Computational identification and experimental verification of a novel signature based on SARS-CoV-2-related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients.

Background: Early research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined. Methods: We acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-CoV-2 score (Cov-2S) signature across The Cancer Genome Atlas and datasets GSE72094, GSE68465, and GSE31210. Comprehensive multi-omics analysis, including assessments of genetic mutations and copy number variations, was conducted to deepen our understanding of the prognosis signature. We also analyzed the response of different Cov-2S subgroups to immunotherapy and identified targeted drugs for these subgroups, advancing personalized medicine strategies. The expression of Cov-2S genes was confirmed through qRT-PCR, with GGH emerging as a critical gene for further functional studies to elucidate its role in LUAD. Results: Out of 34 differentially expressed CRGs identified, 16 correlated with overall survival. We utilized 10 machine learning algorithms, creating 101 combinations, and selected the RFS as the optimal algorithm for constructing a Cov-2S based on the average C-index across four cohorts. This was achieved after integrating several essential clinicopathological features and 58 established signatures. We observed significant differences in biological functions and immune cell statuses within the tumor microenvironments of high and low Cov-2S groups. Notably, patients with a lower Cov-2S showed enhanced sensitivity to immunotherapy. We also identified five potential drugs targeting Cov-2S. In vitro experiments revealed a significant upregulation of GGH in LUAD, and its knockdown markedly inhibited tumor cell proliferation, migration, and invasion. Conclusion: Our research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor's local immune condition, and supports clinical decision-making in tumor therapies.

A review of obstructive sleep apnea and lung cancer: epidemiology, pathogenesis, and therapeutic options.

Despite undeniable advances in modern medicine, lung cancer still has high morbidity and mortality rates. Lung cancer is preventable and treatable, and it is important to identify new risk factors for lung cancer, especially those that can be treated or reversed. Obstructive sleep apnea (OSA) is a very common sleep-breathing disorder that is grossly underestimated in clinical practice. It can cause, exacerbate, and worsen adverse outcomes, including death and various diseases, but its relationship with lung cancer is unclear. A possible causal relationship between OSA and the onset and progression of lung cancer has been established biologically. The pathophysiological processes associated with OSA, such as sleep fragmentation, intermittent hypoxia, and increased sympathetic nervous excitation, may affect normal neuroendocrine regulation, impair immune function (especially innate and cellular immunity), and ultimately contribute to the occurrence of lung cancer, accelerate progression, and induce treatment resistance. OSA may be a contributor to but a preventable cause of the progression of lung cancer. However, whether this effect exists independently of other risk factors is unclear. Therefore, by reviewing the literature on the epidemiology, pathogenesis, and treatment of lung cancer and OSA, we hope to understand the relationships between the two and promote the interdisciplinary exchange of ideas between basic medicine, clinical medicine, respiratory medicine, sleep medicine, and oncology.

The impact of social support on benefit finding among patients with advanced lung cancer and their caregivers: based on actor-partner interdependence mediation model.

PURPOSE: Advanced lung cancer and its treatment serve as a sudden stressful event that profoundly impacts the psychological experience of both the patients and their primary caregiver. This study used dyadic analyses to explore the dyadic effects of social support on benefit finding and whether hope level mediates the patient-caregiver dyads in advanced lung cancer. METHODS: Two hundred ninety-five pairs of patients with advanced lung cancer and primary caregivers completed the Social Support Rating Scale (SSRS), the Herth Hope Index (HHI), and the Benefit Finding Scale (BFS). Dyadic analyses were conducted using structural equation modelling based on the actor-partner interdependence mediation model. RESULTS: The results indicated that for both patients (B = 0.259, 95% CI = 0.135-0.423, P < 0.001) and their primary caregivers (B = 0.596, 95% CI = 0.403-0.838, P < 0.001), hope level mediated the actor effect of social support on benefit finding; social support was positively associated with hope level and further enhanced benefit finding. Regarding partner effects (B = 0.242, 95% CI = 0.119-0.404, P < 0.001), primary caregivers' social support significantly indirectly affected patients' benefit finding through patients' hope level. CONCLUSION: There is an interaction between social support, hope level, and benefit finding in patients with advanced lung cancer and their primary caregivers. Healthcare professionals ought to be vigilant in recognizing patients and caregivers who are vulnerable, have limited social support, and possess diminished hope levels. At the same time, nurses should provide timely psychological support and counseling to patients and their caregivers, encourage them to actively participate in social activities, and inspire their confidence and hope in life, thus improving their benefit findings.

PD-L1 inhibitors combined with whole brain radiotherapy in patients with small cell lung cancer brain metastases: Real-world evidence.

BACKGROUND: Numerous studies have demonstrated that brain metastases patients may benefit from intracranial radiotherapy combined with immune checkpoint inhibitors (ICIs). However, it is unclear whether this treatment is effective for patients with small cell lung cancer brain metastases (SCLC-BMs). METHODS: We conducted a retrospective study by analyzing medical records of patients with SCLC-BMs from January 1, 2017 to June 1, 2022. Data related to median overall survival (mOS), median progression-free survival (mPFS), and intracranial progression-free survival (iPFS) were analyzed. RESULTS: A total of 109 patients were enrolled, of which 60 received WBRT and 49 received WBRT-ICI. Compared to the WBRT alone cohort, the WBRT-ICI cohort showed longer mOS (20.4 months vs. 29.3 months, p = 0.021), mPFS (7.9 months vs. 15.1 months, p < 0.001), and iPFS (8.3 months vs. 16.5 months, p < 0.001). Furthermore, WBRT-ICI cohort had a better response rate for both BMs. (p = 0.035) and extracranial diseases (p < 0.001) compared to those receiving WBRT alone. Notably, the use of WBRT before ICI was associated with longer mOS compared to the use of WBRT after ICI (23.3 months for the ICI-WBRT group vs. 34.8 months for the WBRT-ICI group, p = 0.020). CONCLUSION: Our results indicated that WBRT combined with immunotherapy improved survival in SCLC-BMs patients compared to WBRT monotherapy. Administering WBRT prior to ICI treatment is associated with improved survival outcomes compared to WBRT following ICI treatment, for patients with SCLC-BMs. These findings highlight the significance of conducting further prospective researches on combination strategies of intracranial radiotherapy and ICI in SCLC-BMs patients.

Pamiparib as consolidation treatment after concurrent chemoradiotherapy of limited-stage small cell lung cancer: a single-arm, open-label phase 2 trial.

BACKGROUND: Small cell lung cancer (SCLC) is highly invasive with poor prognosis, and its treatment has historically been hindered due to the absence of targetable driver genomic alterations. However, the high genomic instability and replication stress in SCLC have made poly(ADP-ribose) polymerases (PARPs) inhibitors a focus of research. Pamiparib is an orally available PARP1/2 inhibitor with high selectivity, strong PARP trapping activity, and excellent brain penetration. Utilizing pamiparib as consolidation maintenance therapy in limited-stage SCLC holds promise for improving survival outcomes and offering a viable therapeutic approach. METHODS: This single-arm, open-label phase II trial will enroll patients aged 18-75 years with histologically/cytologically confirmed, limited-stage SCLC who have not progressed following definitive platinum-based cCRT and have an ECOG PS of 0 or 1. Patients will be excluded if they have histologically confirmed mixed SCLC or NSCLC, or have undergone previous tumor resection, or can be treated with surgery or stereotactic body radiation therapy/stereotactic ablative radiation therapy. Participants will receive pamiparib 40 mg twice daily every 3 weeks within 2 to 6 weeks after cCRT for up to 1 year or until disease progression according to RECIST v1.1. The primary endpoint is the 1-year progression-free survival (PFS) rate assessed by investigators per RECIST v1.1. Secondary endpoints include PFS, objective response rate, and duration of response assessed by investigators per RECIST 1.1, overall survival, time to distant metastasis, and safety. DISCUSSION: The study will provide valuable data on the feasibility, safety, and effectiveness of pamiparib as a consolidation therapy after cCRT in patients with LS-SCLC. The correlation between molecular typing or gene expression profile of the disease and curative response will be further explored. TRIAL REGISTRATION: NCT05483543 at clinicaltrials.gov.

Triple-induction treatment for locally advanced non-small cell lung cancer: a case report of pathological complete response.

BACKGROUND: In patients with resectable stage III non-small cell lung cancer (NSCLC), induction chemoimmunotherapy followed by surgical resection has shown unprecedented rates of pathological response and event-free survival. However, a triple-induction including radiochemotherapy and immunotherapy followed by surgical resection has not been routinely established in clinical practice. CASE PRESENTATION: We report the case of a 47-year-old patient with stage IIIA NSCLC who was treated in a combined concept including induction concurrent radiochemotherapy, followed by 4 cycles of pembrolizumab and subsequent intrapericardial left-sided pneumonectomy. Histological analysis revealed a pathological complete response. CONCLUSIONS: The case demonstrates that the combination of neoadjuvant chemo-, radio- and immunotherapy in advanced NSCLC may lead to a relevant down-staging and may enable a R0-resection of a borderline resectable tumor. However, the combination of four different treatment modalities requires resilience and a good performance status. A triple induction treatment may be a promising option for selected patients with locally advanced NSCLC and good performance status.

Discovering single cannabidiol or synergistic antitumor effects of cannabidiol and cytokine-induced killer cells on non-small cell lung cancer cells.

Introduction: A multitude of findings from cell cultures and animal studies are available to support the anti-cancer properties of cannabidiol (CBD). Since CBD acts on multiple molecular targets, its clinical adaptation, especially in combination with cancer immunotherapy regimen remains a serious concern. Methods: Considering this, we extensively studied the effect of CBD on the cytokine-induced killer (CIK) cell immunotherapy approach using multiple non-small cell lung cancer (NSCLC) cells harboring diverse genotypes. Results: Our analysis showed that, a) The Transient Receptor Potential Cation Channel Subfamily V Member 2 (TRPV2) channel was intracellularly expressed both in NSCLC cells and CIK cells. b) A synergistic effect of CIK combined with CBD, resulted in a significant increase in tumor lysis and Interferon gamma (IFN-g) production. c) CBD had a preference to elevate the CD25+CD69+ population and the CD62L_CD45RA+terminal effector memory (EMRA) population in NKT-CIK cells, suggesting early-stage activation and effector memory differentiation in CD3+CD56+ CIK cells. Of interest, we observed that CBD enhanced the calcium influx, which was mediated by the TRPV2 channel and elevated phosphor-Extracellular signal-Regulated Kinase (p-ERK) expression directly in CIK cells, whereas ERK selective inhibitor FR180204 inhibited the increasing cytotoxic CIK ability induced by CBD. Further examinations revealed that CBD induced DNA double-strand breaks via upregulation of histone H2AX phosphorylation in NSCLC cells and the migration and invasion ability of NSCLC cells suppressed by CBD were rescued using the TRPV2 antagonist (Tranilast) in the absence of CIK cells. We further investigated the epigenetic effects of this synergy and found that adding CBD to CIK cells decreased the Long Interspersed Nuclear Element-1 (LINE-1) mRNA expression and the global DNA methylation level in NSCLC cells carrying KRAS mutation. We further investigated the epigenetic effects of this synergy and found that adding CBD to CIK cells decreased the Long Interspersed Nuclear Element-1 (LINE-1) mRNA expression and the global DNA methylation level in NSCLC cells carrying KRAS mutation. Conclusions: Taken together, CBD holds a great potential for treating NSCLC with CIK cell immunotherapy. In addition, we utilized NSCLC with different driver mutations to investigate the efficacy of CBD. Our findings might provide evidence for CBD-personized treatment with NSCLC patients.

Soluble immune-checkpoint factors: a potential immunotherapy biomarker.

There is unmet need for additional biomarkers to better select patients with non-small cell lung cancer (NSCLC) that are likely to benefit from immunotherapy in order to improve patient outcomes, reduce patient toxicity, and relieve the growing burden of healthcare costs. In this issue of the JCI, Hayashi and colleagues evaluated soluble forms of the immune checkpoint molecules PD-L1, PD-1, and CTLA-4 in the plasma of patients with advanced NSCLC who had been treated with anti-PD-1/L1 therapy. The findings suggest that these soluble immune-checkpoint factors may provide a complementary biomarker to PD-L1 IHC, although application into the clinic may not be straightforward.

An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy.

Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient's survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD.

Area-based disparities in non-small-cell lung cancer survival.

BACKGROUND: In the Nordic countries, universal healthcare access has been effective in reducing socioeconomic disparities in non-small-cell lung cancer (NSCLC) management. However, other factors, such as proximity to healthcare facilities, may still affect access to care. This study aimed at investigating the influence of residential area on NSCLC survival. METHODS: This population-based study utilized hospital records to identify NSCLC patients who underwent their initial treatment at Vaasa Central Hospital between January 1, 2016, and December 31, 2020. Patients were categorized based on their postal codes into urban areas (≤50 km from the hospital) and rural areas (>50 km from the hospital). Survival rates between these two groups were compared using Cox regression analysis. RESULTS: A total of 321 patients were included in the study. Patients residing in rural areas (n = 104) exhibited poorer 12-month survival rates compared to their urban counterparts (n = 217) (unadjusted Hazard Ratio [HR]: 1.38; 95% Confidence Interval [CI]: 1.01-1.89; p = 0.042). After adjusting for factors such as performance status, frailty, and stage at diagnosis in a multivariate Cox regression model, the adjusted HR increased to 1.47 (95% CI: 1.07-2.01; p = 0.017) for patients living in rural areas compared to those in urban areas. INTERPRETATION: The study findings indicate that the distance to the hospital is associated with increased lung cancer mortality. This suggests that geographical proximity may play a crucial role in the disparities observed in NSCLC survival rates. Addressing these disparities should involve strategies aimed at improving healthcare accessibility, particularly for patients residing in rural areas, to enhance NSCLC outcomes and reduce mortality.

Trajectories of Health Care Contact Days for Patients With Stage IV Non-Small Cell Lung Cancer.

Importance: Patients with stage IV non-small cell lung cancer (NSCLC) experience substantial morbidity and mortality. Contact days (ie, the number of days with health care contact outside the home) measure how much of a person's life is consumed by health care, yet little is known about patterns of contact days for patients with NSCLC. Objective: To describe the trajectories of contact days in patients with stage IV NSCLC and how trajectories vary by receipt of cancer-directed treatment in routine practice. Design, Setting, and Participants: A retrospective, population-based decedent cohort study was conducted in Ontario, Canada. Participants included adults aged 20 years or older who were diagnosed with stage IV NSCLC (January 1, 2014, to December 31, 2017) and died (January 1, 2014, to December 31, 2019); there was a maximum 2-year follow-up. Data analysis was conducted from February 22 to August 16, 2023. Exposure: Systemic cancer-directed therapy (yes or no) and type of therapy (chemotherapy vs immunotherapy vs targeted therapy). Main Outcomes and Measures: Contact days (days with health care contact, outpatient or institution-based, outside the home) were identified through administrative data. The weekly percentage of contact days and fitted models with cubic splines were quantified to describe trajectories from diagnosis until death. Results: A total of 5785 decedents with stage IV NSCLC were included (median age, 70 [IQR 62-77] years; 3108 [53.7%] were male, and 1985 [34.3%] received systemic therapy). The median overall survival was 108 (IQR, 49-426) days, median contact days were 36 (IQR, 21-62), and the median percentage that were contact days was 33.3%. A median of 5 (IQR, 2-10) days were spent with specialty palliative care. Patients who did not receive systemic therapy had a median overall survival of 66 (IQR, 34-130) days and median contact days of 28 (IQR, 17-44), of which a median of 5 (IQR, 2-9) days were spent with specialty palliative care. Overall and for subgroups, normalized trajectories followed a U-shaped distribution: contact days were most frequent immediately after diagnosis and before death. Patients who received targeted therapy had the lowest contact day rate during the trough (10.6%; vs immunotherapy, 15.4%; vs chemotherapy, 17.7%). Conclusions and Relevance: In this cohort study, decedents with stage IV NSCLC had a median survival in the order of 3.5 months and spent 1 in every 3 days alive interacting with the health care system outside the home. These results highlight the need to better support patients and care partners, benchmark appropriateness, and improve care delivery.

Segmentation of patients with small cell lung cancer into responders and non-responders using the optimal cross-validation technique.

BACKGROUND: The timing of treating cancer patients is an essential factor in the efficacy of treatment. So, patients who will not respond to current therapy should receive a different treatment as early as possible. Machine learning models can be built to classify responders and nonresponders. Such classification models predict the probability of a patient being a responder. Most methods use a probability threshold of 0.5 to convert the probabilities into binary group membership. However, the cutoff of 0.5 is not always the optimal choice. METHODS: In this study, we propose a novel data-driven approach to select a better cutoff value based on the optimal cross-validation technique. To illustrate our novel method, we applied it to three clinical trial datasets of small-cell lung cancer patients. We used two different datasets to build a scoring system to segment patients. Then the models were applied to segment patients into the test data. RESULTS: We found that, in test data, the predicted responders and non-responders had significantly different long-term survival outcomes. Our proposed novel method segments patients better than the standard approach using a cutoff of 0.5. Comparing clinical outcomes of responders versus non-responders, our novel method had a p-value of 0.009 with a hazard ratio of 0.668 for grouping patients using the Cox proportion hazard model and a p-value of 0.011 using the accelerated failure time model which approved a significant difference between responders and non-responders. In contrast, the standard approach had a p-value of 0.194 with a hazard ratio of 0.823 using the Cox proportion hazard model and a p-value of 0.240 using the accelerated failure time model indicating the responders and non-responders do not differ significantly in survival. CONCLUSION: In summary, our novel prediction method can successfully segment new patients into responders and non-responders. Clinicians can use our prediction to decide if a patient should receive a different treatment or stay with the current treatment.

Rational and design of prophylactic cranial irradiation (PCI) and brain MRI surveillance versus brain MRI surveillance alone in patients with limited-stage small cell lung cancer achieving complete remission (CR) of tumor after chemoradiotherapy: a multicenter prospective randomized study.

BACKGROUND: Prophylactic cranial irradiation (PCI) is part of standard care in limited-stage small cell lung cancer (SCLC) at present. As evidence from retrospective studies increases, the benefits of PCI for limited-stage SCLC are being challenged. METHODS: A multicenter, prospective, randomized controlled study was designed. The key inclusion criteria were: histologically or cytologically confirmed small cell carcinoma, age ≥ 18 years, KPS ≥ 80, limited-stage is defined as tumor confined to one side of the chest including ipsilateral hilar, bilateral mediastinum and supraclavicular lymph nodes, patients have received definitive thoracic radiotherapy (regardless of the dose-fractionation of radiotherapy used) and chemotherapy, evaluated as complete remission (CR) of tumor 4-6 weeks after the completion of chemo-radiotherapy. Eligible patients will be randomly assigned to two arms: (1) PCI and brain MRI surveillance arm, receiving PCI (2.5 Gy qd to a total dose of 25 Gy in two weeks) followed by brain MRI surveillance once every three months for two years; (2) brain MRI surveillance alone arm, undergoing brain MRI surveillance once every three months for two years. The primary objective is to compare the 2-year brain metastasis-free survival (BMFS) rates between the two arms. Secondary objectives include 2-year overall survival (OS) rates, intra-cranial failure patterns, 2-year progression-free survival rates and neurotoxicity. In case of brain metastasis (BM) detect during follow-up, stereotactic radiosurgery (SRS) will be recommended if patients meet the eligibility criteria. DISCUSSION: Based on our post-hoc analysis of a prospective study, we hypothesize that in limited-stage SCLC patients with CR after definitive chemoradiotherapy, and ruling out of BM by MRI, it would be feasible to use brain MRI surveillance and omit PCI in these patients. If BM is detected during follow-up, treatment with SRS or whole brain radiotherapy does not appear to have a detrimental effect on OS. Additionally, this approach may reduce potential neurotoxicity associated with PCI.

Anti-EGFR ScFv functionalized exosomes delivering LPCAT1 specific siRNAs for inhibition of lung cancer brain metastases.

Brain metastasis (BM) is one of the leading causes of cancer-related deaths in patients with advanced non-small cell lung cancer (NSCLC). However, limited treatments are available due to the presence of the blood-brain barrier (BBB). Upregulation of lysophosphatidylcholine acyltransferase 1 (LPCAT1) in NSCLC has been found to promote BM. Conversely, downregulating LPCAT1 significantly suppresses the proliferation and metastasis of lung cancer cells. In this study, we firstly confirmed significant upregulation of LPCAT1 in BM sites compared to primary lung cancer by analyzing scRNA dataset. We then designed a delivery system based on a single-chain variable fragment (scFv) targeting the epidermal growth factor receptor (EGFR) and exosomes derived from HEK293T cells to enhance cell-targeting capabilities and increase permeability. Next, we loaded LPCAT1 siRNA (siLPCAT1) into these engineered exosomes (exoscFv). This novel scFv-mounted exosome successfully crossed the BBB in an animal model and delivered siLPCAT1 to the BM site. Silencing LPCAT1 efficiently arrested tumor growth and inhibited malignant progression of BM in vivo without detectable toxicity. Overall, we provided a potential platform based on exosomes for RNA interference (RNAi) therapy in lung cancer BM.

Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung cancer (NSCLC), and identifying candidates likely responding to this advanced treatment is of important clinical significance. The current multi-institutional study aims to develop a deep learning model to predict pathologic complete response (pCR) to neoadjuvant immunotherapy in NSCLC based on computed tomography (CT) imaging and further prob the biologic foundation of the proposed deep learning signature. A total of 248 participants administrated with neoadjuvant immunotherapy followed by surgery for NSCLC at Ruijin Hospital, Ningbo Hwamei Hospital, and Affiliated Hospital of Zunyi Medical University from January 2019 to September 2023 were enrolled. The imaging data within 2 weeks prior to neoadjuvant chemoimmunotherapy were retrospectively extracted. Patients from Ruijin Hospital were grouped as the training set (n = 104) and the validation set (n = 69) at the 6:4 ratio, and other participants from Ningbo Hwamei Hospital and Affiliated Hospital of Zunyi Medical University served as an external cohort (n = 75). For the entire population, pCR was obtained in 29.4% (n = 73) of cases. The areas under the curve (AUCs) of our deep learning signature for pCR prediction were 0.775 (95% confidence interval [CI]: 0.649 - 0.901) and 0.743 (95% CI: 0.618 - 0.869) in the validation set and the external cohort, significantly superior than 0.579 (95% CI: 0.468 - 0.689) and 0.569 (95% CI: 0.454 - 0.683) of the clinical model. Furthermore, higher deep learning scores correlated to the upregulation for pathways of cell metabolism and more antitumor immune infiltration in microenvironment. Our developed deep learning model is capable of predicting pCR to neoadjuvant chemoimmunotherapy in patients with NSCLC.

Role of STING in the treatment of non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is a prevalent form of lung cancer. Patients with advanced NSCLC are currently being treated with various therapies, including traditional radiotherapy, chemotherapy, molecular targeted therapies and immunotherapy. However, a considerable proportion of advance patients who cannot benefit from them. Consequently, it is essential to identify a novel research target that offers an encouraging perspective. The stimulator of interferon genes (STING) has emerged as such a target. At present, it is confirmed that activating STING in NSCLC tumor cells can impede the proliferation and metastasis of dormant tumor cells. This review focuses on the role of STING in NSCLC treatment and the factors influencing its activation. Additionally, it explores the correlation between STING activation and diverse therapy modalities for NSCLC, such as radiotherapy, chemotherapy, molecular targeted therapies and immunotherapy. Furthermore, it proposes the prospect of innovative therapy methods involving nanoparticles, with the aim of using the features of STING to develop more strategies for NSCLC therapy.

Correlation of distribution characteristics and dynamic changes of gut microbiota with the efficacy of immunotherapy in EGFR-mutated non-small cell lung cancer.

BACKGROUND: The effects of gut microbiota and metabolites on the responses to immune checkpoint inhibitors (ICIs) in advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) have been studied. However, their effects on EGFR-mutated (EGFR +) NSCLC remain unknown. METHODS: We prospectively recorded the clinicopathological characteristics of patients with advanced EGFR + NSCLC and assessed potential associations between the use of antibiotics or probiotics and immunotherapy efficacy. Fecal samples were collected at baseline, early on-treatment, response and progression status and were subjected to metagenomic next-generation sequencing and ultra-high-performance liquid chromatography-mass spectrometry analyses to assess the effects of gut microbiota and metabolites on immunotherapy efficacy. RESULTS: The clinical data of 74 advanced EGFR + NSCLC patients were complete and 18 patients' fecal samples were dynamically collected. Patients that used antibiotics had shorter progression-free survival (PFS) (mPFS, 4.8 vs. 6.7 months; P = 0.037); probiotics had no impact on PFS. Two dynamic types of gut microbiota during immunotherapy were identified: one type showed the lowest relative abundance at the response time point, whereas the other type showed the highest abundance at the response time point. Metabolomics revealed significant differences in metabolites distribution between responders and non-responders. Deoxycholic acid, glycerol, and quinolinic acid were enriched in responders, whereas L-citrulline was enriched in non-responders. There was a significant correlation between gut microbiota and metabolites. CONCLUSIONS: The use of antibiotics weakens immunotherapy efficacy in patients with advanced EGFR + NSCLC. The distribution characteristics and dynamic changes of gut microbiota and metabolites may indicate the efficacy of immunotherapy in advanced EGFR + NSCLC.

A population study comparing tracheal and lung adenoid cystic carcinoma.

BACKGROUND: Thoracic adenoid cystic carcinoma (ACC) is rare, and the differences between tracheal and lung lesions have not been fully understood. METHODS: Patients were identified from a Chinese cancer center (FUSCC) (2005-2022) and the Surveillance, Epidemiology, and End Results (SEER) database (2000-2019). Incidence was calculated and trends were quantified. Clinicopathological features and overall survival (OS) were analyzed. Nomograms predicting OS were constructed. RESULTS: Totally, 55 tracheal adenoid cystic carcinoma (TACC) and 25 lung and bronchus adenoid cystic carcinoma (LACC) were included in a Chinese cohort, 121 TACC and 162 LACC included in the SEER cohort. There were larger tumor sizes, more lymph nodes and distant metastases for LACC than TACC patients. TACC patients are more likely to get local treatments. Patients with LACC had significantly worse median OS than patients with TACC (SEER cohort: 68.0 months vs. 109.0 months, p = 0.001, Chinese cohort: 62.9 months vs. 124.8 months, p = 0.061). Age, lymph node metastasis, distant metastasis and local treatment were identified as independent prognostic factors for OS of TACC. Distant metastasis and local treatment were identified for LACC. Specifically, surgery alone or in combination with radiotherapy is crucial for improving survival in both TACC and LACC. Only TACC benefits from radiotherapy alone, while chemotherapy does not improve survival for either. The nomograms constructed using these factors revealed good prognostic accuracy. CONCLUSIONS: LACC is more aggressive and has a worse prognosis than TACC. TACC patients have more opportunities for local treatment, which is important for the prognosis of both TACC and LACC. Nomograms were created for TACC and LACC to aid in personalized survival predictions and clinical decisions.