Outcome Of Non-small Cell Lung Cancer Patients Research Articles

Transcriptional phenocopies of deleterious KEAP1 mutations correlate with survival outcomes in lung cancer treated with immunotherapy.

Co-occurring mutations in KEAP1 and STK11KRAS have emerged as determinants of survival outcomes in non-small cell lung cancer (NSCLC) patients treated with immunotherapy. However, these mutational contexts identify a fraction of non-responders to immune checkpoint inhibitors. We hypothesized that KEAP1 wild-type tumors recapitulate the transcriptional footprint of KEAP1 mutations, and that this KEAPness phenotype can determine immune responsiveness with higher precision compared to mutation-based models. The TCGA was used to infer the KEAPness phenotype and explore its immunological correlates at the pan-cancer level. The association between KEAPness and survival outcomes was tested in two independent cohorts of advanced NSCLC patients treated with immunotherapy and profiled by RNA-Seq (SU2C n=153; OAK/POPLAR n=439). The NSCLC TRACERx421 multi-region sequencing study (tumor regions n=947) was used to investigate evolutionary trajectories. KEAPness-dominant tumors represented 50% of all NSCLCs and were associated with shorter progression-free survival (PFS) and overall survival (OS) compared to KEAPness-free cases in independent cohorts of NSCLC patients treated with immunotherapy (SU2C PFS P=0.042, OS P=0.008; OAK/POPLAR PFS P=0.0014, OS P<0.001). Patients with KEAPness tumors had survival outcomes comparable to those with KEAP1-mutant tumors. In the TRACERx421, KEAPness exhibited limited transcriptional intratumoral heterogeneity and immune exclusion, resembling the KEAP1-mutant disease. This phenotypic state occurred across genetically divergent tumors, exhibiting shared and private cancer genes under positive selection when compared to KEAP1-mutant tumors. We identified a KEAPness phenotype across evolutionary divergent tumors. KEAPness outperforms mutation-based classifiers as a biomarker of inferior survival outcomes in NSCLC patients treated with immunotherapy.

Artificial intelligence (AI) -powered H&amp;E whole-slide image (WSI) analysis of tertiary lymphoid structure (TLS) to predict response to immunotherapy in non-small cell lung cancer (NSCLC).

3135 Background: Recent data indicate that immune cells present in the TLS within the tumor microenvironment (TME) could potentially serve as a favorable predictor for immune checkpoint inhibitor (ICI) therapy. To examine this further, AI model was created to provide an assessment of TLS in H&amp;E WSI, and to determine its correlation with survival outcomes of NSCLC patients treated with ICI. Methods: We collected H&amp;E-stained WSI of primary and metastatic tumors and clinical data in a retrospective study of advanced-stage NSCLC patients treated with ICI (with or without chemotherapy) at Northwestern University from May 2015 to November 2022. When evaluating the TLS status in the biopsy specimen collected from the lymph nodes (LNs), TLSs were only considered if they were admixed with tumor cells and located distant from the residual parenchyma, ensuring the exclusion of innate lymphoid follicles. Following the assessment of the presence of TLS by a pathologist, the identical WSIs were evaluated by the AI-powered H&amp;E WSI analyzer. We used Lunit SCOPE IO, an AI-powered H&amp;E WSI analyzer developed using 21,096 H&amp;E stained WSIs, which can segment various classes of tissue area including TLS within the TME. Survival analysis was performed using Kaplan-Meier curves, and differences in survival outcomes among TLS groups were evaluated using the log-rank test. Results: In this analysis, out of a total of 73 patients, 24 (33%) cases were identified as containing TLS (TLS +) by the AI analyzer. In contrast, the pathologist classified 17 (23%) cases as TLS+. The AI model demonstrated an accuracy of 84.9% (with a sensitivity of 88.2% and specificity of 83.9%) in identifying the presence of TLS compared to the pathologist's interpretation. The median value of the proportion of TLS area within TME (TLSP) in samples containing TLS was 0.418% (Q1: 0.228%, Q3: 1.311%). TLSP was not found to be correlated with survival outcomes. The number of clusters of TLS was not found to be correlated with survival outcomes. Conclusions: AI-powered TLS analysis can be potentially utilized as a predictive biomarker of survival outcomes of NSCLC patients treated with ICI. [Table: see text]

Effect of body mass index and cholesterol-rich apolipoprotein-B-containing lipoproteins on clinical outcome in NSCLC patients treated with immune checkpoint inhibitors-based therapy: A retrospective analysis.

Obesity and hypercholesterolemia are linked to unfavor clinical outcomes. Recent studies declared the paradox that high body mass index (BMI) and serum cholesterol were independently connected to better clinical outcome of immune checkpoint inhibitors (ICIs) monotherapy in non-small cell lung cancer (NSCLC). The aim of the study is to investigate the prognosis of BMI and serum cholesterol in ICIs-based therapy. This is a retrospective study of 95 NSCLC patients treated with ICIs-based therapy at the Department of Oncology and Lung Cancer Center of China-Japan Friendship Hospital. Treatment efficacy was assessed using durable clinical benefit (DCB) versus nondurable benefit (NDB), best response (active vs. nonactive), and progression-free survival (PFS). The prognostic value of BMI, LDL-C, and RC was determined by multivariate regression analyses, while controlling for confounding factors including age, gender, diabetes status, smoking history, and statin usage. BMI was considered a confounding factor in the analysis when examining the impact of lipoproteins. In our study, we found that in the whole group, BMI ≥25 kg/m2 was linked to a higher risk of poor therapeutic response (OR = 5.92, 95% CI 1.99-19.51, p.val = 0.002) and shorter progression-free survival (HR = 3.00, 95% CI 1.59-5.68, p.val = 0.001). In addition, low levels of RC were associated with better therapeutic response (OR = 0.12, 95% CI 0.02-0.64, p.val = 0.019), while low levels of serum LDL-C were found to predict longer PFS (HR = 0.40, 95% CI 0.19-0.82, p.val = 0.012). These associations were consistent in advanced NSCLC patients receiving ICIs and chemotherapy. Our study suggest that BMI ≥25 kg/m2 and elevated levels of apoB-containing lipoproteins, including LDL-C and RC, could potentially serve as useful prognostic markers for predicting poor treatment outcomes in advanced NSCLC patients treated with the combination of chemotherapy and ICIs.

The efficacy and safety of continuous intravenous infusion of rh-endostatin combined with platinum-based doublet chemotherapy for advanced non-small-cell lung cancer

BackgroundPlatinum-based doublet chemotherapy is commonly used in the treatment of non-small cell lung cancer (NSCLC). A growing body of evidence indicates that incorporating antiangiogenic agents into platinum-based chemotherapy may enhance the survival outcomes for NSCLC patients. However, the optimal administration protocol for intravenous recombinant human endostatin (rh-endostatin), an antiangiogenic agent, remains uncertain at present.AimThis study aims to investigate the efficacy and safety of 5-d continuous intravenous infusion of rh-endostatin in combination with chemotherapy for patients with advanced NSCLC. The predictive biomarkers for this treatment regimen were further probed.MethodsThis prospective, single-arm multicenter study enrolled a total of 48 patients with advanced NSCLC who were histologically or cytologically confirmed but had not received any prior treatment from January 2021 to December 2022. Prior to the chemotherapy, these patients received a continuous intravenous infusion of rh-endostatin (210 mg) over a period of 120 h, using an infusion pump. The chemotherapy regimen included a combination of platinum with either pemetrexed or paclitaxel, given in 21-day cycles. The primary endpoint of the study was median progression-free survival (mPFS), and the secondary endpoints included median overall survival (mOS), objective response rate (ORR), disease control rate (DCR), and assessment of adverse events (AEs).ResultsThe mPFS was 6.5 months (95% confidence interval (CI): 3.8–9.1 m) while the mOS was 12.3 months (95% CI: 7.6–18.5 m). The ORR and DCR was 52.1% and 75.0%, respectively. Leukopenia (52.1%), anemia (33.3%), and thrombocytopenia (20.8%) were the most common adverse effects and these toxicities were deemed acceptable and manageable. In addition, a correlation was noted between elevated serum carcinoembryonic antigen (CEA) levels and decreased PFS and OS.ConclusionsThe incorporation of a 5-day continuous intravenous infusion of rh-endostatin into platinum-based doublet chemotherapy has demonstrated both safety and efficacy in the treatment of advanced NSCLC. Furthermore, the baseline serum levels of CEA may potentially function as a predictor for the efficacy of rh-endostatin when combined with chemotherapy in NSCLC patients.ClinicalTrials.govNCT05574998.

JAML promotes the antitumor role of tumor-resident CD8+ T cells by facilitating their innate-like function in human lung cancer

Tissue-resident memory CD8+T cells (CD8+TRMs) are thought to play a crucial role in cancer immunosurveillance. However, the characteristics of CD8+TRMs in the tumor microenvironment (TME) of human non-small cell lung cancer (NSCLC) remain unclear. Here, we report that CD8+TRMs accumulate explicitly and exhibit a unique gene expression profile in the TME of NSCLC. Interestingly, these tumor-associated CD8+TRMs uniquely exhibit an innate-like phenotype. Importantly, we found that junction adhesion molecule-like (JAML) provides an alternative costimulatory signal to activate tumor-associated CD8+TRMs via combination with cancer cell-derived CXADR (CXADR Ig-like cell adhesion molecule). Furthermore, we demonstrated that activating JAML could promote the expression of TLR1/2 on CD8+TRMs, inhibit tumor progression and prolong the survival of tumor-bearing mice. Finally, we found that higher CD8+TRMs and JAML expression in the TME could predict favorable clinical outcomes in NSCLC patients. Our study reveals an intrinsic bias of CD8+TRMs for receiving the tumor-derived costimulatory signal in the TME, which sustains their innate-like function and antitumor role. These findings will shed more light on the biology of CD8+TRMs and aid in the development of potential targeted treatment strategies for NSCLC.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer.

Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Abstract 7530: Harmonization radiomics models to predict tumor response in non-small cell lung cancer (NSCLC) patients treated with immunotherapy

Abstract Background: Precise prediction of immunotherapy response in non-small cell lung cancer (NSCLC) is crucial for personalized treatment. This study investigates the application of pretreatment CT-based radiomics and use of harmonization model in predicting these outcomes in NSCLC patients receiving immunotherapy. Methods: This retrospective study examined data from 152 stage III-IV NSCLC patients undergoing immunotherapy. Patient responses were categorized using immune-related RECIST (irRECIST) criteria into durable responders (complete response [CR], partial response [PR], or stable disease [SD]) for at least 24 weeks and non-responders. Tumor segmentation was performed using LIFEx software (IMIV/CEA, Orsay, France). 3D-radiomic features were extracted from both the tumor and surrounding 1 cm thick peritumoral regions. The Random Forest (RF) algorithm was employed to develop a classification model to differentiate between responders and non-responders. A harmonization model was deployed to account for the scanner-related differences by using spleen and normal lung signals. The dataset was divided into a training set (75%) and a test set (25%). Bootstrapping with 1,000 iterations was performed to estimate the model's performance by calculating the median and 95% confidence interval (CI) estimate. The accuracy of the model's predictions was evaluated by creating a confusion matrix. The model's performance was assessed by calculating the sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and area under the ROC curve (AUC) for response prediction. Results: A total of 152 patients were analyzed. 87 (57.23%) were female and 65 (42.76%) were male. The median age was 59 years. Histology types included were: 111 Adenocarcinoma (73%), 27 Squamous cell carcinoma (17.8%), and 14 other types (9.2%). The model achieved a sensitivity of 0.63, a specificity of 0.59, a PPV of 0.51, and NPV of 0.7 for response prediction of NSCLC patients receiving immunotherapy. The AUC of 0.61 indicates that the model may discriminate between responders and non-responders with an accuracy of 61%. Conclusion: This study demonstrates the potential of radiomics and the use of harmonization models to predict immunotherapy responses in NSCLC patients, offering insights into personalized treatment approaches. Larger studies are needed to validate our findings and the utility of harmonization models in predicting a tumor response. Citation Format: Monica Yadav, Jeeyeon Lee, Peter Haseok Kim, Seyoung Lee, Taegyu Um, Salie Lee, Maria Jose Chuchuca, Trie Arni Djunadi, Liam Il-Young Chung, Jisang Yu, Darren Rodrigues, Nicolo Gennaro, Leeseul Kim, Myungwoo Nam, Youjin Oh, Sungmi Yoon, Zunairah Shah, Yuchan Kim, Ilene Hong, Jessica Jang, Grace Kang, Amy Cho, Soowon Lee, Timothy Hong, Cecilia Nam, Yury S Velichko, Young Kwang Chae. Harmonization radiomics models to predict tumor response in non-small cell lung cancer (NSCLC) patients treated with immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7530.

Abstract 641: SCD1 upregulation due to STK11/KEAP1 loss upregulates SLC7A11 and causes deregulation of fatty acid metabolism leading to ferroptosis evasion

Abstract Introduction: Non-small cell lung cancer (NSCLC) with co-occurring loss-of-function (LOF) mutations in serine/threonine kinase 11 (STK11) and Kelch-like ECH-associated protein1 (KEAP1) (SK) are notably aggressive and unresponsive to chemo and immunotherapy, in current care standards. Novel therapeutic strategies are in demand to improve the outcomes for SK co-mutant NSCLC patients. We reported earlier that SK LOF mutations enhance cell proliferation and tumor growth in xenograft lung cancer models. We also found the ferroptosis evasion genes are enriched, and targeting ferroptosis regulators is a therapeutic opportunity in SK co-mutant NSCLC. Methods: We used CRISPR/Cas9 gene editing to create stable knockouts of STK11 (SKO), KEAP1 (KKO) or both (DKO), non-targeting control (NTC) in two NSCLC lines. We performed an in vitro druggable genome library CRISPR screening in the same NSCLC lines. We performed kinase profiling and RNA-seq in the cell lines to depict the transcriptomic and proteomic landscape, followed by western blotting and qRT-PCR validation. We also performed BODIPY/C11 assay and lipidomics to explore the ferroptosis and metabolic landscape of SK co-mutant NSCLC models. Results: Stearoyl CoA desaturase-1 (SCD1) was the top CRISPR screen hit, a critical modulator of fatty acid metabolism and ferroptosis evasion. SCD1 expression is significantly higher in NSCLC tissue than adjacent normal tissue (p&amp;lt;0.0001), and high SCD1 expression correlates with poorer prognosis in patients with NSCLC (p=0.027). GSEA from the bulk RNA sequencing in SK co-mutant cells pre-and post-SCD1 inhibitor treatment showed SCD1 inhibition leads to upregulation of the glutathione and glutamic acid pathways compared to NTC cells. Moreover, SK co-mutant cells have a significantly higher expression of SLC7A11, enabling cystine uptake and subsequent conversion to cysteine, essential for maintaining redox balance and cell survival. Hence, SK co-mutant cells are more resistant to cysteine depletion than NTC cells. SCD1 inhibition causes a decrease in SLC7A11 expression exclusively in DKO cells. Eventually, SCD1 inhibition leads to global metabolomic changes in SK co-mutant cells, including key pathways involved in lipid and glucose metabolism. Finally, genetic and pharmacological inhibition of SCD1 prevents tumor growth and sensitizes DKO cells to ferroptosis inducers like erastin. Conclusions: Our findings highlight the importance of the SCD1-SLC7A11 axis in regulating ferroptosis in SK co-mutant models. Current data impact our understanding of ferroptosis in NSCLC and its ability to target SCD1 or ferroptosis in cancer treatment. Compounds such as inhibitors of SLC7A11 (Erastin/IKE) are safe to use with acceptable toxicity and established doses. Hence, our study will facilitate the translation of ferroptosis inducers or SCD1 inhibitors in clinical trials. Citation Format: Utsav Sen, Charles Coleman, Dan Hasson, Triparna Sen. SCD1 upregulation due to STK11/KEAP1 loss upregulates SLC7A11 and causes deregulation of fatty acid metabolism leading to ferroptosis evasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 641.

5-Methylcytosine transferase NSUN2 drives NRF2-mediated ferroptosis resistance in non-small cell lung cancer

RNA 5-methylcytosine (m5C) is an abundant chemical modification in mammalian RNAs and plays crucial roles in regulating vital physiological and pathological processes, especially in cancer. However, the dysregulation of m5C and its underlying mechanisms in non-small cell lung cancer (NSCLC) remain unclear. Here we identified that NSUN2, a key RNA m5C methyltransferase, is highly expressed in NSCLC tumor tissue. We found elevated NSUN2 expression levels strongly correlate with tumor grade and size, predicting poor outcomes for NSCLC patients. Furthermore, RNA-seq and subsequent confirmation studies revealed the antioxidant-promoting transcription factor NRF2 is a target of NSUN2, and depleting NSUN2 increases the sensitivity of NSCLC cells to ferroptosis activators both in vitro and in vivo. Additionally, knockdown of NSUN2 markedly inhibits the expression of NRF2 mRNA and protein. Intriguingly, the methylated-RIP-qPCR assay results indicated that NRF2 mRNA has a higher m5C level when NSUN2 is overexpressed in NSCLC cells, but shows no significant changes in the NSUN2 methyltransferase-deficient group. Mechanistically, we confirmed that NSUN2 upregulates the expression of NRF2 by enhancing the stability of NRF2 mRNA through the m5C modification within its 5'UTR region recognized by the specific m5C reader protein YBX1, rather than influencing its translation. In subsequent rescue experiments, we show knocking down NRF2 diminished the proliferation, migration, and ferroptosis tolerance mediated by NSUN2 overexpression. In conclusion, our study unveils a novel regulatory mechanism in which NSUN2 sustains NRF2 expression through an m5C-YBX1-axis, suggesting that targeting NSUN2 and its regulated ferroptosis pathway might offer promising therapeutic strategies for NSCLC patients.

A novel investigation into the negative impact of opioid use on the efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer patients

ObjectiveImmune checkpoint inhibitors (ICIs) have effectively improved the clinical outcome of advanced non-small cell lung cancer (NSCLC). Opioids are commonly used for pain relief in cancer patients. This study aims to clarify the prognostic impact of opioid use in advanced NSCLC patients receiving ICI therapy. MethodsA systematic literature review was carried out using online databases before July 2023. The meta-analysis was used to clarify the correlation of opioid use with the overall survival (OS) or progression-free survival (PFS) of ICI-treated NSCLC patients, both of which were determined using hazard ratios (HRs) coupled with 95 % confidence intervals (CIs). Then, an independent cohort enrolling 181 NSCLC patients was utilized for validation. Finally, a comprehensive bioinformatics analysis based on TCGA cohort was performed to investigate the prognostic significance of opioid target genes (OTGs) and their correlation with immune infiltration in NSCLC patients. ResultsA total of 8 studies enrolling 1174 patients were included in the meta-analysis. Opioid use was negatively associated with worse PFS (HR = 2.16, 95 %CI: 1.26–3.71) and OS (HR = 2.02, 95 %CI: 1.54–2.63) in ICI-treated NSCLC patients. The retrospective validation confirmed the above result and identified opioid use as an independent unfavorable predictor for PFS and OS in both the entire cohort and ICI subgroup. The bioinformatic analysis identified 14 prognostic OTGs (CYP17A1, PDYN, PYCARD, FGA, NTSR1, FABP1, HPCA, PENK, PDGFB, LIN7A, FKBP5, TYMS, CACNA1H and LDHA), most of which were correlated with immune infiltration in NSCLC. A risk model was constructed based on 14 OTGs and found to effectively stratify the clinical outcome in both the training and validation set, independent of age, gender and TNM staging system. The model was also significantly correlated with infiltration of activated dendritic cells, neutrophils and tumor infiltrating lymphocytes. Finally, a nomogram was constructed based on the model, age, gender and TNM stage, which could predict well the 1-, 3- and 5-year survival of NSCLC patients. ConclusionOpioid use is correlated with the poor clinical outcome in ICI-treated NSCLC patients. Precise pain management is highly advocated and opioids are recommended to be cautiously used in these patients. OTGs have the potential to be prognostic biomarkers for NSCLC patients and their role in tumor immunity needs to be further investigated.

PD-L1 mRNA derived from tumor-educated platelets as a potential immunotherapy biomarker in non-small cell lung cancer.

To date, the role of programmed death ligand-1 (PD-L1) messenger RNA (mRNA) derived from tumor-educated platelets (TEPs) has not been well investigated in patients with advanced non-small cell lung cancer (NSCLC). A few reports have examined whether mRNA in TEPs can predict the clinical responses of patients with advanced NSCLC following immunotherapy. This study aimed to identify novel biomarkers to improve the clinical benefits and outcomes of NSCLC patients. Advanced NSCLC patients receiving a combination of immunotherapy and chemotherapy, or immunotherapy alone as a first- or second-line treatment at the Fudan University Shanghai Cancer Center were enrolled in this study. All the patients had wild-type epidermal growth factor receptor/anaplastic lymphoma kinase. The patients were enrolled in clinical trials for immune checkpoint inhibitors (ICIs), including nivolumab, pembrolizumab, atezolizumab, durvalumab, tremelimumab, and camrelizumab. Tumoral PD-L1 expression was tested by immunohistochemistry (PD-L1 22C3 pharmDx kit, Agilent, Santa Clara, CA, USA) in archived tissue samples, when available, to calculate the tumor proportion scores (TPSs). RNA and exosomal RNA of blood were isolated before immunotherapy using the Yunying RNA extraction kit (Yunying Medicine, Shanghai, China). The concentration and quality of the RNA was determined using a Qubit fluorometer (Life Technologies, Carlsbad, CA, USA). Finally, we analyzed the predictive value of TEP-derived PD-L1 mRNA expression and association with the level of the tumoral PD-L1 expression. In total, 72 patients were enrolled in this study. Most of the patients were male (n=54, 75.0%), had adenocarcinoma (n=49, 68.1%). We found there was no significant correlation between the TEP-derived mRNA of PD-L1 and tumoral PD-L1 expression based on the results of the Pearson Correlation test (r=-0.19, P=0.233). Based on the median of PD-L1 mRNA, 72 patients were divided into a high PD-L1 group and a low PD-L1 group. We found that 19 patients (44.4%) responded to immunotherapy [partial response or progression-free survival (PFS) >6 months] in the high PD-L1 group, but only five patients (13.9%) responded to immunotherapy in the low PD-L1 group (P<0.01). The median PFS of the low PD-L1 group was lower than that of the high PD-L1 group (2.8 vs. 8.3 months, P<0.001). For the patients who were treated with immunotherapy alone (n=64), a similar PFS advantage was observed in the high PD-L1 group (2.8 vs. 8.0 months, P=0.002). This article presented the first data on TEP-derived PD-L1 mRNA in advanced NSCLC patients following immunotherapy and showed the potential advantage of using it as the surrogate biomarker for predicting the PFS and overall survival of patients following immunotherapy.

Lipid alterations play a role in the integration of PD-1/PD-L1 inhibitors and anlotinib for the treatment of advanced non–small-cell lung cancer

BackgroundStudies have shown that integrating anlotinib with programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors enhances survival rates among progressive non–small-cell lung cancer (NSCLC) patients lacking driver mutations. However, not all individuals experience clinical benefits from this therapy. As a result, it is critical to investigate the factors that contribute to the inconsistent response of patients. Recent investigations have emphasized the importance of lipid metabolic reprogramming in the development and progression of NSCLC.MethodsThe objective of this investigation was to examine the correlation between lipid variations and observed treatment outcomes in advanced NSCLC patients who were administered PD-1/PD-L1 inhibitors alongside anlotinib. A cohort composed of 30 individuals diagnosed with advanced NSCLC without any driver mutations was divided into three distinct groups based on the clinical response to the combination treatment, namely, a group exhibiting partial responses, a group manifesting progressive disease, and a group demonstrating stable disease. The lipid composition of patients in these groups was assessed both before and after treatment.ResultsSignificant differences in lipid composition among the three groups were observed. Further analysis revealed 19 differential lipids, including 2 phosphatidylglycerols and 17 phosphoinositides.ConclusionThis preliminary study aimed to explore the specific impact of anlotinib in combination with PD-1/PD-L1 inhibitors on lipid metabolism in patients with advanced NSCLC. By investigating the effects of using both anlotinib and PD-1/PD-L1 inhibitors, this study enhances our understanding of lipid metabolism in lung cancer treatment. The findings from this research provide valuable insights into potential therapeutic approaches and the identification of new therapeutic biomarkers.

Multi-institutional prognostic modeling of survival outcomes in NSCLC patients treated with first-line immunotherapy using radiomics

BackgroundImmune checkpoint inhibitors (ICIs) have emerged as one of the most promising first-line therapeutics in the management of non-small cell lung cancer (NSCLC). However, only a subset of these patients responds to ICIs, highlighting the clinical need to develop better predictive and prognostic biomarkers. This study will leverage pre-treatment imaging profiles to develop survival risk models for NSCLC patients treated with first-line immunotherapy.MethodsAdvanced NSCLC patients (n = 149) were retrospectively identified from two institutions who were treated with first-line ICIs. Radiomics features extracted from pretreatment imaging scans were used to build the predictive models for progression-free survival (PFS) and overall survival (OS). A compendium of five feature selection methods and seven machine learning approaches were utilized to build the survival risk models. The concordance index (C-index) was used to evaluate model performance.ResultsFrom our results, we found several combinations of machine learning algorithms and feature selection methods to achieve similar performance. K-nearest neighbourhood (KNN) with ReliefF (RL) feature selection was the best-performing model to predict PFS (C-index = 0.61 and 0.604 in discovery and validation cohorts), while XGBoost with Mutual Information (MI) feature selection was the best-performing model for OS (C-index = 0.7 and 0.655 in discovery and validation cohorts).ConclusionThe results of this study highlight the importance of implementing an appropriate feature selection method coupled with a machine learning strategy to develop robust survival models. With further validation of these models on external cohorts when available, this can have the potential to improve clinical decisions by systematically analyzing routine medical images.

Meta-analysis of the efficacy of postoperative adjuvant chemotherapy for stage IB non-small cell lung cancer.

Many clinical trials have shown that postoperative adjuvant chemotherapy can provide a survival benefit for patients with stage IB non-small cell lung cancer. However, whether adjuvant chemotherapy should be routinely given after surgery remains controversial. Therefore, we performed a meta-analysis to investigate the efficacy of adjuvant chemotherapy versus surgery alone for stage IB non-small cell lung cancer (NSCLC). Relevant retrospective studies or randomized controlled trial comparing the efficacy of postoperative adjuvant chemotherapy versus observation on the survival outcomes of NSCLC patients up to October 30, 2023 were searched in PubMed, Web of Science, EMBASE, Cochrane Library, VIP database, Wanfang database, and China National Knowledge Internet database. Patient survival data, population characteristics, and other relevant information were extracted, and data were analyzed using Review Manager 5.4. The primary endpoints included overall survival, disease-free survival, and recurrence-free survival. A total of 13 randomized controlled trials or cohort studies including 19,442 patients were included. The results of the meta-analysis showed that postoperative adjuvant chemotherapy in patients with stage IB NSCLC had better overall survival (odds ratio [OR] = 1.25, 95% confidence interval [CI] 1.19-1.31, P < .00001) and disease-free survival or recurrence-free survival (OR = 1.57, 95% CI 1.3-1.9, P < .00001) compared with observation; and the 4-year survival rate of patients who received postoperative adjuvant chemotherapy was better than the observation group (OR = 1.52, 95% CI 1.05-2.18, P = .03); and the 8-year survival rate of patients receiving postoperative adjuvant chemotherapy (OR = 1.5, 95% CI 0.94-2.4, P = .09) was comparable to the observation group. Receiving postoperative adjuvant chemotherapy improved people's survival and prolonged disease-free survival and recurrence-free survival in patients with stage IB non-small cell lung cancer compared with surgery alone.

Meta-Analysis of Circulating Tumor Cell PD-L1 Expression and the Association with Clinical Outcomes in Non-Small Cell Lung Cancer.

Programmed death ligand-1 (PD-L1) expression on circulating tumor cells (CTCs) has been suggested to provide prognostic information in non-small cell lung cancer (NSCLC), but consensus relative to treatment outcomes is lacking. We conducted the first comprehensive meta-analysis exploring its potential as a prognostic and predictive marker, and assessed the concordance between PD-L1 + CTCs and paired tumor tissue in NSCLC patients. A comprehensive search was applied to PubMed and EMBASE to identify 26 studies that evaluated PD-L1 + CTCs and their association with survival outcomes in 1236 NSCLC patients. The meta-analysis estimated a mean PD-L1 + CTCs detection rate of 61% (95% CI, 49-72). Subgroup analysis based on treatment showed that PD-L1 + CTCs was not significantly associated with better overall survival (OS) in NSCLC patients treated with immune checkpoint inhibitors (ICIs) (Hazard Ratio (HR) = 0.96, 95% CI, 0.35-2.65, P = 0.944), but was predictive of worse OS in those treated with other therapies (HR = 2.11, 95% CI, 1.32-3.36, P = 0.002). Similarly, PD-L1 + CTCs was not significantly associated with superior progressing free survival (PFS) in NSCLCs treated with ICIs (HR = 0.67, 95% CI, 0.41-1.09, P = 0.121), but was significantly associated with shorter PFS in patients treated with other therapies (HR = 1.91, 95% CI, 1.24-2.94, P = 0.001). The overall estimate for the concordance between PD-L1 expression on CTCs and tumor cells was 63% (95% CI, 44-80). The average detection rate of PD-L1 + CTCs was comparable to the rate of PD-L1 expression in NSCLC tumors. There was a trend towards better PFS in ICI-treated NSCLC patients with PD-L1 + CTCs. Larger longitudinal studies on the association of PD-L1 + CTCs with clinical outcomes in NSCLC patients treated with ICIs are warranted.

Bone mineral density as an individual prognostic biomarker in NSCLC patients treated with immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICIs) have left a deep impression in the treatment of non-small cell lung cancer (NSCLC), however, not all patients benefit from it. The purpose of this study was to investigate the prognostic value of baseline bone mineral density (BMD) derived from chest computed tomography (CT) scans in NSCLC patients treated with ICIs. This study included patients with advanced NSCLC who underwent ICI treatment at the Wuhan Union Hospital from March 2020 to October 2022. Baseline BMD was evaluated at non-contrast chest CT at the level of first lumbar vertebra. Patients were divided into BMD-lower group and BMD-higher group according to the optimal cutoff value calculated by X-tile software. Baseline characteristics of the two groups were compared and variables between the two groups were balanced by propensity score matching (PSM) analysis. We calculated the objective response rate (ORR) and disease control rate (DCR) of the two groups and analyzed overall survival (OS) and progression-free survival (PFS) using BMD and other clinical indexes through Cox regression models and Kaplan-Meier survival curves. A total of 479 patients were included in this study, and all patients were divided into BMD-lower group (n=270) and BMD-higher group (n=209). After PSM analysis, each group consisted of 150 patients. ORR (43.3% vs. 43.5% before PSM, P = 0.964; 44.7% vs. 44.7% after PSM, P = 1.000) and DCR (91.1% vs. 94.3% before PSM, P = 0.195; 93.3% vs. 96.7% after PSM, P =0.190) were similar in two groups. There was no statistically significant relationship between BMD degree and PFS before (16.0 months vs. 18.0 months, P = 0.067) and after PSM analysis (17.0 months vs. 19.0 months, P = 0.095). However, lower BMD was associated with shorter OS both before (20.5 months vs. 23.0 months, P< 0.001) and after PSM analysis (20.0 months vs. 23.0 months, P = 0.008). Lower baseline BMD is associated with worse clinical outcomes in NSCLC patients treated with ICIs. As a reliable and easily obtained individual prognostic biomarker, BMD can become a routine detection indicator before immunotherapy.

Optimum timing of lung resection surgery following SARS-CoV-2 infection for non-small cell lung cancer.

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on postoperative recovery of non-small cell lung cancer (NSCLC) is need to be understood, thereby informing the optimal timing of surgical decision-making during the COVID-19 pandemic for NSCLC patients. This study reports the postoperative outcomes of surgical NSCLC patients with preoperative SARS-CoV-2 infection. This single-center retrospective cohort study included 241 NSCLC patients who underwent lobectomy or sub-lobectomy between December 1, 2022 and February 14, 2023. Surgical outcomes of patients with preoperative SARS-CoV-2 infection (stratified by the time from diagnosis of SARS-CoV-2 infection to surgery) were compared with those without preoperative SARS-CoV-2 infection. The primary outcomes were total postoperative complications and postoperative pulmonary complications (PPCs), the secondary outcomes included operation time, total postoperative drainage and time, length of hospital stay (LOS), 30-day and 90-day postoperative symptoms. This study included 153 (63.5%) patients with preoperative SARS-CoV-2 infection and 88 (36.5%) patients without previous SARS-CoV-2 infection. In patients with a preoperative SARS-CoV-2 diagnosis, the incidence of total postoperative complications (OR, 3.00; 95% CI, 1.12-8.01; p = 0.028) and PPCs (OR, 4.20; 95% CI, 1.11-15.91; p = 0.035) both increased in patients infected having surgery within 2 weeks compared with non-infection before surgery. However, patients who underwent lung resection more than 2 weeks after SARS-CoV-2 diagnosis had a similar risk of postoperative complications and surgical outcomes with those non-infection before surgery. This is the first study to provide evidence regarding the optimum timing of lung resection surgery and assessing early outcomes after surgery in NSCLC patients with SARS-CoV-2 infection. Our study documents that the SARS-CoV-2 infection did not complicate surgical procedures for lung cancer, and suggest that lung surgery should be postponed at least 2 weeks after SARS-CoV-2 infection for NSCLC patients.

Predictors of Early Hospice or Death in Patients With Inoperable Lung Cancer Treated With Curative Intent

IntroductionTreatment for inoperable stage II to III non-small cell lung cancer (NSCLC) involves chemo-radiotherapy (CRT). However, some patients transition to hospice or die early during their treatment course. We present a model to prognosticate early poor outcomes in NSCLC patients treated with curative-intent CRT. Methods and MaterialsAcross a statewide consortium, data was prospectively collected on stage II to III NSCLC patients who received CRT between 2012 and 2019. Early poor outcomes included hospice enrollment or death within 3 months of completing CRT. Logistic regression models were used to assess predictors in prognostic models. LASSO regression with multiple imputation were used to build a final multivariate model, accounting for missing covariates. ResultsOf the 2267 included patients, 128 experienced early poor outcomes. Mean age was 71 years and 59% received concurrent chemotherapy. The best predictive model, created parsimoniously from statistically significant univariate predictors, included age, ECOG, planning target volume (PTV), mean heart dose, pretreatment lack of energy, and cough. The estimated area under the ROC curve for this multivariable model was 0.71, with a negative predictive value of 95%, specificity of 97%, positive predictive value of 23%, and sensitivity of 16% at a predicted risk threshold of 20%. ConclusionsThis multivariate model identified a combination of clinical variables and patient reported factors that may identify individuals with inoperable NSCLC undergoing curative intent chemo-radiotherapy who are at higher risk for early poor outcomes.

Circular RNA circRANGAP1/miR-512-5p/SOD2 Axis Regulates Cell Proliferation and Migration in Non-small Cell Lung Cancer (NSCLC)

AbstractNon-small cell lung cancer (NSCLC) is the most prevalent histology type of lung cancer worldwide, accounting for 18% of total cancer-related deaths estimated by GLOBOCAN in 2020. CircRNAs have emerged as potent regulators of NSCLC development. CircRANGAP1 (hsa_circ_0001235/hsa_circ_0063526) is a potential biomarker for NSCLC identified by microarray dataset analysis. Here, we investigated the biological functions of circRANGAP1 in NSCLC development and elucidated the associated competing endogenous RNA (ceRNA) mechanisms. We found that circRANGAP1 expression was upregulated in NSCLC tissues and cells, which was inversely correlated with carcinogenesis and poor clinical outcome of NSCLC patients. CircRANGAP1 knockdown inhibited NSCLC migration by regulating miR-512-5p/SOD2 axis. In conclusion, circRANGAP1 facilitated NSCLC tumorigenesis and development by sponging miR-512-5p to upregulate SOD2 expression. Suppression of circRANGAP1 expression by si-circRANGAP1 treatment could be a strategy to inhibit NSCLC development and metastasis.

Clinical markers predict the efficacy of several immune checkpoint inhibitors in patients with non-small cell lung cancer in China.

Immune checkpoint inhibitors (ICIs) are one of the most significant oncological treatment modalities as a result of the rapid advancement of immunotherapy. Programmed Cell Death-Ligand 1 (PD-L1) and tumor mutational burden (TMB) have emerged as key markers for predicting the efficacy and prognosis of ICIs in non-small cell lung cancer (NSCLC), and the predictive role of tumor-infiltrating lymphocytes (TILs) has also received significant attention. However, the prognosis of some individuals cannot be determined by these indicators; for instance, some patients with low PD-L1 expression also benefit from longer survival. Therefore, the purpose of this research was to investigate the connection between new haematological and pathological markers and clinical outcomes in NSCLC patients receiving ICIs. Seventy-six patients with stage III-IV NSCLC treated with ICIs were included in this study. We used the Mann-Whitney test, COX regression and Kaplan-Meier analysis to retrospectively analyze peripheral blood indicators and survival prognostic data of 76 patients in order to investigate the relationship between baseline neutrophil-to-lymphocyte ratio (NLR) and the efficacy of ICIs. To investigate the correlation between CXCL13, CXCR5, CD8 and the efficacy of ICIs, we assessed the expression levels of aforementioned indicators in biopsied tissues of 10 non-small cell lung tumors by immunohistochemistry (IHC) and immunofluorescence (IF) and performed statistical analysis. Disease control rate (DCR) was higher in patients with baseline NLR <3.4 (p=0.016) and neutrophil percentage <71% (P=0.015). Baseline NLR (HR=2.364, P=0.003) and neutrophil percentage (HR=2.824, P=0.013) had the greatest influence on patients' survival prognosis, with baseline NLR exhibiting a stronger predictive value (AUC=0.717), according to univariate and multifactorial COX regression analyses of progression-free survival (PFS) and overall survival (OS). In NSCLC tissues, higher expression of CXCL13 was associated with better clinical outcomes (P=0.032) and higher expression of CD8 was associated with prolonged survival (P=0.022). Low baseline NLR in peripheral blood and high expression of CD8 in tissues are associated with longer PFS and may have a potential predictive value for patients with stage III-IV NSCLC using ICIs.