Survival Of Lung Cancer Patients Research Articles

Cuproptosis in lung cancer: therapeutic options and prognostic models.

Lung cancer (LC) is a serious threat to mankind. The survival of LC patients is still poor despite the enormous efforts that have been made to develop novel treatments. A copper-dependent cell death termed cuproptosis is distinct from known programmed cell death (PCD). Cuproptosis is induced by the disruption of the binding of copper to lipoylated tricarboxylic acid (TCA) cycle proteins of mitochondrial respiratory chains. Potential approaches for treating LC are inducing cell cuproptosis and targeting cell copper death mechanisms. Thus, in this review, we summarize the systemic and cellular metabolic processes of copper. We highlight the possible therapeutic options of employing copper ionophores and chelators for inducing cuproptosis. Moreover, we summarize the prognostic models based on cuproptosis-related genes (CRGs) to identify promising biomarkers for tumor diagnosis and therapy. This review aims to provide a comprehensive summary of CRGs-based prognostic models and promising therapeutic options for cuproptosis induction in LC.

WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy.

Immune checkpoint inhibitors (ICIs) are now one of the standards of care for patients with lung cancer and have greatly improved both progression-free and overall survival, although of the patients respond to the treatment, and some face acute adverse events. Although a few predictive biomarkers have integrated the clinical workflow, they require additional modalities on top of whole-slide images and lack efficiency or robustness. In this work, we propose a biomarker of immunotherapy outcome derived solely from the analysis of histology slides. We develop a three-step framework, combining contrastive learning and nonparametric clustering to distinguish tissue patterns within the slides, before exploiting the adjacencies of previously defined regions to derive features and train a proportional hazards model for survival analysis. We test our approach on an in-house dataset of 193 patients from 5 medical centers and compare it with the gold standard tumor proportion score (TPS) biomarker. On a fivefold cross-validation (CV) of the entire dataset, the whole-slide image-based survival analysis for patients treated with immunotherapy (WhARIO) features are able to separate a low- and a high-risk group of patients with a hazard ratio (HR) of 2.29 ( to 3.56), whereas the TPS 1% reference threshold only reaches a HR of 1.81 ( to 2.69). Combining the two yields a higher HR of 2.60 ( to 3.94). Additional experiments on the same dataset, where one out of five centers is excluded from the CV and used as a test set, confirm these trends. Our uniquely designed WhARIO features are an efficient predictor of survival for lung cancer patients who received ICI treatment. We achieve similar performance to the current gold standard biomarker, without the need to access other imaging modalities, and show that both can be used together to reach even better results.

Endocrine toxicity is an independent predictor of survival in lung cancer patients treated with immune checkpoint inhibitors

Endocrine toxicity is an independent predictor of survival in lung cancer patients treated with immune checkpoint inhibitors

Integrated meta-analyses of genome-wide effects of PM2.5 in human cells identifies widespread dysregulation of genes and pathways associated with cancer progression and patient survival

Epidemiological studies have consistently shown a positive association between exposure to ambient PM2.5, a major component of air pollution, and various types of cancer. Previous biological research has primarily focused on the association between PM2.5 and lung cancer, with limited investigation into other cancer types. In this study, we conducted a meta-analysis on multiple PM2.5-treated normal human cell lines to identify potential molecular targets and pathways of PM2.5. Our analysis revealed 310 common differentially expressed genes (DEGs) that exhibited significant dysregulation upon exposure to PM2.5. These dysregulated genes covered a diverse range of functional categories, including oncogenes, tumor suppressor genes, and immune-related genes, which collectively contribute to PM2.5-induced carcinogenesis. Pathway enrichment analysis revealed the up-regulation of pathways associated with HIF-1, VEGF, and MAPK signalling, all of which have been implicated in various cancers. Induction in the levels of HIF pathway genes (HIF1⍺, HIF2⍺, VEGFA, BNIP3, EPO and PGK1) upon PM2.5 treatment was also confirmed by qRT-PCR. Furthermore, the construction of a protein-protein interaction (PPI) network unveiled hub genes, such as NQO1 and PDGBRB, that are known to be dysregulated and significantly correlated with overall survival in lung and breast cancer patients, suggesting their potential clinical significance. This study provides a deep insight into how PM2.5-mediated dysregulation of oncogenes or tumor suppressor genes across various human tissues may play an important role in PM2.5-induced carcinogenesis. Further exploration of these dysregulated molecular targets may enhance our understanding of the biological effects of PM2.5 and facilitate the development of preventive strategies and targeted therapies for PM2.5-associated cancers.

Prognostic implications of STK11 with different mutation status and its relationship with tumor-infiltrating immune cells in non-small cell lung cancer.

Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling.

[18F]fluorodeoxyglucose positron emission tomography/computed tomography in combination with clinical data in predicting overall survival in non-small-cell lung cancer patients: A retrospective study

IntroductionPositron emission tomography/computed tomography (PET/CT) has an established role in evaluating patients with lung cancer. The aim of this work was to assess the predictive capability of [18F]Fluorodeoxyglucose ([18F]FDG) PET/CT parameters on overall survival (OS) in lung cancer patients using an artificial neural network (ANN) in parallel with conventional statistical analysis. MethodsRetrospective analysis was performed on a group of 165 lung cancer patients (98M, 67F). PET features associated with the primary tumor: maximum and mean standardized uptake value (SUVmax, SUVmean), total lesion glycolysis (TLG) metabolic tumor volume (MTV) and area under the curve-cumulative SUV histogram (AUC-CSH) and metastatic lesions (SUVmaxtotal, SUVmeantotal, TLGtotal, and MTVtotal) were evaluated. In parallel with conventional statistical analysis (Chi-Square analysis for nominal data, Student's t test for continuous data), the data was evaluated using an ANN. There were 97 input variables in 165 patients using a binary classification of either below, or greater than/equal to median survival post primary diagnosis. Additionally, phantom study was performed to assess the most optimal contouring method. ResultsMales had statistically higher SUVmax (mean: 10.7 vs 8.9; p = 0.020), MTV (mean: 66.5 cm3 vs. 21.5 cm3; p = 0.001), TLG (mean 404.7 vs. 115.0; p = 0.003), TLGtotal (mean: 946.7 vs. 433.3; p = 0.014) and MTVtotal (mean: 242.0 cm3 vs. 103.7 cm3; p = 0.027) than females. The ANN after training and validation was optimised with a final architecture of 4 scaling layer inputs (TLGtotal, SUVmaxtotal, SUVmeantotal and disease stage) and receiving operator characteristic (ROC) analysis demonstrated an AUC of 0.764 (sensitivity of 92.3%, specificity of 57.1%). ConclusionConventional statistical analysis and the ANN provided concordant findings in relation to variables that predict decreased survival. The ANN provided a weighted algorithm of the 4 key features to predict decreased survival. Implication for practiceIdentification of parameters which can predict survival in lung cancer patients might be helpful in choosing the group of patients who require closer look during the follow-up.

Survival and safety analysis of COVID-19 vaccine in Chinese patients with non-small cell lung cancer.

Severe acute respiratory syndrome coronavirus 2 disease (COVID-19) has caused a worldwide challenging and threatening pandemic. We aimed to assess the safety and efficacy of the COVID-19 vaccines in Non-Small Cell Lung Cancer (NSCLC) patients. Patient self-reported adverse events related to vaccines were recorded by follow-up through a uniform questionnaire. Survival analysis was performed by Kaplan-Meier method. A multivariate analysis was performed by the Cox proportional hazard regression model to determine the effect of each variable on the survival of lung cancer patients. A total of 860 patients with NSCLC on treatment were enrolled. Mean age was 57 years in patients with early stage group and 62 years in advanced stage group. The vaccination rate was 71.11% for early-stage patients and 19.48% for advanced-stage patients; most of them (86.5%) received the COVID-19 inactivated virus (Vero cell) vaccine (Coronavac; Sinovac). The most common systemic adverse reaction was weakness. The main reason for vaccine refusal in those unvaccinated patients was concern about the safety of vaccination in the presence of a tumor and undergoing treatment (56.9% and 53.4%). The 1-year disease-free survival (DFS) rate was 100% for vaccinated and 97.4% for unvaccinated early-stage patients. Then we compared the progression-free survival (PFS) of vaccinated (median PFS 9.0 months) and unvaccinated (median PFS 7.0 months) advanced stage patients (p = 0.815). Advanced NSCLC patients continued to be divided into groups receiving radio-chemotherapy, immunotherapy, and targeted therapy, with no statistical difference in PFS between the groups (p > 0.05). The median overall survival (OS) of vaccinated patients was 20.5 months, and that of unvaccinated patients was 19.0 months (p = 0.478) in advanced NSCLC patients. COVID-19 vaccination is safe for Chinese NSCLC patients actively receiving different antitumor treatments without increasing the incidence of adverse reactions, and vaccination does not affect cancer patient survival.

Development and validation of a deep learning-based model to predict response and survival of T790M mutant non-small cell lung cancer patients in early clinical phase trials using electronic medical record and pharmacokinetic data.

Epidermal growth factor receptor (EGFR) T790M mutation is the standard predictive biomarker for third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) treatment. While not all T790M-positive patients respond to third-generation EGFR-TKIs and have a good prognosis, it necessitates novel tools to supplement EGFR genotype detection for predicting efficacy and stratifying EGFR-mutant patients with various prognoses. Mixture-of-experts (MoE) is designed to disassemble a large model into many small models. Meanwhile, it is also a model ensembling method that can better capture multiple patterns of intrinsic subgroups of enrolled patients. Therefore, the combination of MoE and Cox algorithm has the potential to predict efficacy and stratify survival in non-small cell lung cancer (NSCLC) patients with EGFR mutations. We utilized the electronic medical record (EMR) and pharmacokinetic parameters of 326 T790M-mutated NSCLC patients, including 283 patients treated with Abivertinib in phase I (n=177, for training) and II (n=106, for validation) clinical trials and an additional validation cohort 2 comprising 43 patients treated with BPI-7711. Furthermore, 18 patients underwent whole-exome sequencing for biological interpretation of CoxMoE. We evaluated the predictive performance for therapeutic response using the area under the curve (AUC) and the Concordance index (C-index) for progression-free survival (PFS). CoxMoE exhibited AUCs of 0.73-0.83 for predicting efficacy defined by best overall response (BoR) and achieved C-index values of 0.64-0.65 for PFS prediction in training and validating cohorts. The PFS of 198 patients with a low risk [median, 6.0 (range, 1.0-23.3) months in the abivertinib treated cohort; median 16.5 (range, 1.4-27.4) months in BPI-7711 treated cohort] of being non-responder increased by 43% [hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.40-0.78; P=0.0013] and 50% (HR, 0; 95% CI, 0-0; P=0.01) compared to those at high-risk [median, 4.2 (range, 1.0-35) months in the abivertinib treated cohort; median, 11.0 (range, 1.4-25.1) months in BPI-7711 treated cohort]. Additionally, activated partial thromboplastin time (APTT), creatinine clearance (Ccr), monocyte, and steady-state plasma trough concentration utilited to construct model were found significantly associated with drug resistance and aggressive tumor pathways. A robust correlation was observed between APTT and Ccr with PFS (log-rank test; P<0.01) and treatment response (Wilcoxon test; P<0.05), respectively. CoxMoE offers a valuable approach for patient selection by forecasting therapeutic response and PFS utilizing laboratory tests and pharmacokinetic parameters in the setting of early-phase clinical trials. Simultaneously, CoxMoE could predict the efficacy of third-generation EGFR-TKI non-invasively for T790M-positive NSCLC patients, thereby complementing existing EGFR genotype detection.

Impact of lymph node dissection on cancer-specific survival in non-small cell lung cancer patients: a SEER database analysis.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide, and lymph node dissection (LND) is a significant surgical procedure employed in its management. Although some studies suggest benefits of LND, the extent of its impact on survival, the optimal range of lymph nodes to be examined, and the specific patient groups that benefit most remain areas of active debate and investigation. A population-based analysis was conducted using the Surveillance, Epidemiology, and End Results (SEER) database. Patients diagnosed with NSCLC between 2004 and 2017, undergoing primary tumor resection, were included. Descriptive, univariate, and multivariate analyses assessed the effect of LND on survival, and a restricted cubic spline method determined the optimal range for lymph node examination. This study of 37,323 NSCLC patients delved into the impact of LND on lung cancer-specific survival. Key findings revealed a median survival of 19.58 months, with 85% mortality. Baseline characteristics included a majority of White patients (81%), distant stage diagnoses (63%), and 64% with Grade IV tumors. LND emerged as a crucial predictor, influencing survival across age, gender, race, and tumor characteristics. Univariate analysis highlighted its significance, with higher T, N, and M categories, advanced stage, and poorer grade associating with elevated hazard ratios. Multivariate Cox proportional hazards (PH) analysis reinforced LND's impact, showcasing lower hazard ratios post-removal. Hazard ratios for biopsy/aspiration and removal of regional lymph nodes were 0.85 [95% confidence interval (CI): 0.81-0.89; P<0.001] and 0.43 (95% CI: 0.39-0.46; P<0.001), underscoring the protective effect. Visualizations and a U-shaped curve analysis identified an optimal range (24-32 nodes) for examination, emphasizing the nuanced benefits across NSCLC stages. The study findings suggest that LND plays a critical role in improving cancer-specific survival in NSCLC patients, particularly when tailored to the early stages of the disease. The optimal range of lymph nodes examined, between 24 and 32, offers crucial insights for personalized NSCLC treatment strategies and may enhance overall survival. These results underscore the need for refined surgical guidelines that incorporate the extent of LND, supporting the utility of a more personalized approach in NSCLC management.

Prognostic value of pretreatment procalcitonin and neutrophil–lymphocyte ratio in extensive-stage small-cell lung cancer

ABSTRACT Background To investigate the influence of pretreatment neutrophil-to-lymphocyte ratio (NLR) and procalcitonin (PCT) on progression-free survival (PFS) in extensive-stage small-cell lung cancer (SCLC) patients. Method A total of 100 extensive-stage SCLC patients were enrolled in our study. Patients were stratified according to the median values of pretreatment NLR and PCT levels: low NLR group (NLR ≤3.17), high NLR group (NLR＞3.17), low PCT group (PCT ≤0.06; ng/ml), high PCT group (PCT＞0.06; ng/ml). The Kaplan-Meier method and multivariable Cox regression model were used to reveal the prognostic effects of pretreatment NLR and PCT on PFS. Results The median PFS of the total extensive-stage SCLC patients was 6.0 months. The median PFS of low pretreatment NLR group (NLR ≤3.17) was not significantly different from that of high pretreatment NLR group (6.2 months vs 5.8 months; p = .675). Patients with low pretreatment PCT (PCT ≤0.06; ng/ml) had significantly better PFS than patients with high pretreatment PCT (PCT＞0.06; ng/ml) (6.9 months vs 5.7 months; p = .043). With the multivariable Cox regression analysis, the response to first-line chemotherapy (p ≤ .001) and pretreatment PCT (HR = 0.516; 95%CI 0.326–0.817; p = .005) were identified as independent factors associated with PFS. Conclusion Pretreatment PCT is an independent factor associated with PFS in extensive-stage SCLC patients treated with first-line chemotherapy, but pretreatment NLR reflects no significant prognostic value in our study.

Abstract 2749: DHX36 may promote the growth and metastasis of lung cancer

Abstract Introduction: Helicase is a kind of protein molecular motor that widely exists in eukaryotic cells, viruses and bacterial cells, and participates in DNA replication, transcription and other life activities. DHX36, a kind of helicase, is a new homologous gene of human DNA/RNA helicase cloned by our laboratory by homologous molecular cloning which used the sequence of the maleless gene (mle) of Drosophila. Studies have shown that DHX36 upregulates the expression of proto oncogene and promotes the occurrence of cancer. At present, there are few studies on DHX36 in lung cancer. This study aims to clarify the relationship between DHX36 and lung cancer and provide a new molecular target for the diagnosis, treatment and prognosis of lung cancer. Methods: Twenty-eight pairs of clinical tumor samples from lung adenocarcinoma and adjacent tissues were collected, and the protein expression of DHX36 in different tissues was detected by western blot. Correlation between DHX36 expression and survival prognosis of lung cancer patients was analyzed by online database. Over-expression of DHX36 in A549 and H460 cells and knockdown of DHX36 in A549 and H1975 cell lines, then the migration, invasion and growth index of cells were analyzed by real-time cell analyzer. After DHX36 stable knock-down cell line was established in H1975 cells, they were injected into nude mice by subcutaneous injection and tail vein injection respectively at the same time as the control cells, and the growth of subcutaneous tumors and the metastasis of lung tissues in nude mice were recorded and collected respectively. The tissues were analyzed by histology, immunohistochemistry, and western blot. Results: In 28 pairs of clinical lung cancer tumor samples, we found that DHX36 was higher in cancer tissues than in adjacent tissues in 23 pairs, which indicated that DHX36 might be a kind of proto oncogene to promote the occurrence and development of lung cancer. Bioinformatics analysis revealed that the high expression of DHX36 was related to the low survival of lung cancer patients. The results of RTCA showed that the abilities of growth, invasion and migration of cells in the over-expressed DHX36 groups were higher than those in the control groups. After DHX36 was knocked down, the growth, invasion and invasion of lung cancer cells were inhibited. Conclusion: DHX36 is expected to be a new molecular target of lung cancer. Next, we will knock out DHX36 in lung cancer cells to observe the tumor growth and lung metastasis in mice. Citation Format: Ting Li, Na Luo, Jiewen Fu, Chunli Wei, Junjiang Fu. DHX36 may promote the growth and metastasis of lung cancer [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 2749.

Abstract 2642: KEAP1 mutation in lung cancer cells leads to increased immunosuppressive capability

Abstract Considerable advances have been made in lung cancer therapies, but there is still an unmet clinical need to improve survival for lung cancer patients. Immunotherapies have improved survival, although only 20-30% of patients respond to these treatments. Interestingly, cancers with mutations in KEAP1, the negative regulator of the NRF2 cytoprotective pathway, are resistant to immune checkpoint inhibition and correlate with decreased immune cell infiltration. NRF2 is known for promoting an anti-inflammatory phenotype when activated in immune cells, but the study of NRF2 activation in cancer cells has not been adequately assessed. The overall objective of this study is to determine how lung cancer cells with constitutive NRF2 activity interact with the immune microenvironment to promote cancer progression and metastasis. To assess this, we generated CRISPR-edited mouse lung cancer cell lines (Lewis Lung Carcinoma/LL2) with knockouts (KO) of the KEAP1 and NFE2L2 genes. The transcriptomic profiles of 3 KEAP1 KO and 1 NRF2 KO cell lines were compared to the parental wildtype (WT) line using RNA-sequencing. On unsupervised hierarchical clustering of differentially expressed genes, the 3 KEAP1 KO cell lines clustered together and the NRF2 KO clustered with WT cells. Importantly, canonical NRF2 pathway-related genes were significantly increased in KEAP1 KO clones, but the same genes were either decreased or similar to WT in the NRF2 KO clone. We then used flow cytometry to evaluate immunosuppressive surface markers known to suppress T cell function when expressed on cancer cells. Importantly, PD-L1, CD155, CD80, and CD86 were increased in the KEAP1 KO lines compared to WT, but not in the NRF2 KO clone. In addition, the cytokine release profile was differentially regulated in the KEAP1 KO clones in a manner that could alter T cell recruitment and function. These results were also consistent with gene expression in the sequencing dataset. Finally, using an orthotopic allograft model, we completed a preliminary immunophenotyping study of lung tumors for WT, KEAP1 KO, and NRF2 KO cell lines. The activation status of CD8+ T cells and the ratio of CD8+/CD4+CD25+ T cells (a prognostic marker) were decreased in KEAP1 KO tumors. Taken together, these data suggest cancers with KEAP1 mutations may increase tumor growth through suppression of T cells. Citation Format: Christopher John Occhiuto, Karen T. Liby. KEAP1 mutation in lung cancer cells leads to increased immunosuppressive capability [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 2642.

Abstract 5948: FMC-376 a dual inhibitor of ON and OFF states of KRASG12C is broadly active in PDX models of resistance

Abstract KRASG12C is a frequent activating mutation occurring in NSCLC, CRC, PDAC and other tumors that shifts KRAS into the active, GTP-bound (ON) state. KRAS was long considered undruggable until the recent discovery of single acting inhibitors, including those that bind the GDP-bound, inactive (OFF), state of KRASG12C. The most clinically advanced of these first-generation molecules have demonstrated clinical response rates of 37-43% and 6 to 7-month progression-free survival in lung cancer patients. While an important advance, a majority of cancers do not respond, and acquired resistance is common. FMC-376 is a next-generation dual inhibitor of both the ON and OFF states of KRASG12C with the potential to overcome resistance and deliver best-in-class durability of response. FMC-376 was discovered through the application of the FrontierTM platform, which integrates chemoproteomics, machine-learning, and covalent fragment-based drug discovery. FMC-376 is a highly selective, irreversible inhibitor of KRASG12C that covalently binds to the mutant cysteine in KRASG12C and directly blocks the ON and OFF states of the mutant KRAS protein leading to a complete, durable blockade of downstream signaling. This further translates into more durable tumor regressions in vivo in comparison to OFF state inhibitors like sotorasib. Clinical resistance to first-generation inhibitors that can only bind the OFF state of KRASG12C has been associated with multiple mechanisms that drive upregulation of ON state KRASG12C. These known drivers of resistance include activating co-mutation/amplification/fusions of receptor tyrosine kinases, amplification of KRASG12C and non-mutational mechanisms that lead to paradoxical activation of KRASG12C due to release of negative feedback control upon KRAS inhibition, often referred to as adaptive resistance. In addition, multiple mutations that may act independently of KRAS are also associated with resistance. These include mutation of KEAP1, CDKN2A, SMARCA4, PI3K, PTEN, MTOR, HRAS, NRAS, RAF, and MAPK. In vivo profiling of FMC-376 against a panel KRASG12C mutant patient derived xenograft (PDX) models of NSCLC, CRC and PDAC, has demonstrated that dual inhibition of both ON and OFF KRASG12C leads to complete suppression and regression of tumors carrying a broad spectrum of known genomic and non-genomic (adaptive) drivers of clinical resistance to OFF state KRASG12C inhibitors. FMC-376 a clinical stage dual inhibitor of ON and OFF state KRASG12C has the potential to overcome limitations of single acting and OFF state KRASG12C inhibitors. Citation Format: Yan Wang, Richard M. Neve, Jocelyn Staunton, Kevin R. Webster. FMC-376 a dual inhibitor of ON and OFF states of KRASG12C is broadly active in PDX models of resistance [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 5948.

Abstract 5194: Pre-operative markers extracted from extracellular vesicles related with lung cancer relapse

Abstract Background: Pre- and post-operative immunotherapy have been a new standard of care for lung cancer patients. On the other hand, post-operative Osimertinib; EGFR-TKI therapy had obtained new evidence to the EGFR mutant lung cancer patients. Both treatments revealed to make patient survival prolonged. However, there are quite a lot patients who had experienced disease relapse, despite of multimodal therapy. Extracellular vesicles (EVs) have reported to have potent for searching a new target to cancers. Purpose: Exploration of novel risk factors related with post-operative recurrence of lung cancer. Methods: We retrospectively examined patient background, disease-free survival, overall survival, and preoperative liquid biopsy analysis in lung cancer patients who underwent surgery at Kanazawa University Hospital between January 2017 and May 2020, in whom preoperative chemotherapy was not administered. EVs were extracted from 500 μl serum within 7 days before surgery using MagCapture Exosome isolation Kit PS Ver.2 (FUJIFILM). First, we focused the six cases that had the 3 phase samples: preoperative, disease free and relapse phase. According to the EV concentrations calculated by BCA method, comprehensive protein assessment of these subjects was performed using shotgun mass spectrometry. Secondly, all cases’ prognosis were analyzed in connection with the detected marker using Dot blotting. Results: All EV samples from primary 6 cases were able to be detected and median concentration of those was 27 μg/ml (9-82). We focused on three factors (LCEV1-3) among the 6 cases analysis, when we disease fluctuation. Among LCEV1-3 examination to all preoperative samples, LCEV2 had been related with disease recurrence. Discussions: EVs contain amount of information such as cancer biomarker. Not only that, these factors may have a potency for therapeutic target. Further investigations are needed. Citation Format: Hayato Koba, Shigeki Nanjo, Seiji Yano. Pre-operative markers extracted from extracellular vesicles related with lung cancer relapse [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 5194.

Abstract 114: Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu)

Abstract Our goal is to identify, in situ, the regulatory genes that dictate the onset age and growth rate of spontaneously arising tumors to implement new intervention strategies. For genetic linkage analysis, we crossed HER2(neu) Tg mice with Diversity Outbred (DO) mice, an outbred population comprised of 8 founding strains (A/J, C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, WSB/EiJ) maintained by non-sibling crossing to ensure each mouse is genetically unique. Using R/QTL package, we linked Quantitative Trait Loci (QTL) in Chr 1 and X with tumor onset age, and a Chr 10 QTL with tumor growth rate. The Chr1 (=human Chr2) QTL was linked to human breast cancer diagnosis in 11 Genome-Wide Association Studies (GWAS; the human GWAS catalog, https://www.ebi.ac.uk/gwas/). Because human GWAS data is deficient in Chr X mapping and also does not assess tumor growth rate as a trait, the QTL loci identified in mouse Chr X and 10 were discoveries beyond the capacity of human GWAS. In total, we identified 26 candidate genes across the 3 QTL. For clinical validation, the genes were analyzed with CodeAI (Caris LS) which associated cancer patient clinical data with candidate gene expression. We found 21/26 genes significantly associated with the survival of patients with primary (n=3,533) and/or metastatic (n=4,870) breast cancers and 17/26 were associated with lung cancer (n=11,334) survival, with 13 overlapping genes between lung and breast cancer, indicating broad applicability of these candidate genes. We interrogated the immune status in BALB NeuT and (BALBxPWK)F1 NeuT mice because the F1 mice developed tumors around 9 wk, much earlier than the 14 wk observed in BALB NeuT mice. Surprisingly, (BALBxPWK)F1 mice responded to cancer vaccines more vigorously. Single cell RNA (scRNA) libraries from (BALBxPWK)F1 NeuT tumors showed an expanded lymphocyte cluster (12%), compared with BALB NeuT (2%) and an enrichment of T cell activation genes. These findings may reflect a deficiency in tumor cell recognition by the activated anti-tumor effectors and a window of opportunity for correction. Of the 21 candidate genes, LILRB4, a myeloid cell checkpoint molecule, was of particular interest. Expression of LILRB4 is predictive of patient survival in both breast and lung cancer. Using scRNA sequencing, we found this transmembrane receptor expressed primarily by tumor infiltrating myeloid cells. In a reported scRNA sequencing dataset (GSE161529), LILRB4 was expressed by infiltrating macrophages in human breast cancers, and is also correlated with reduced survival. In a PAN Cancer ATACseq dataset (Corces et al., 2018), promoter accessibility of LILRB4 was associated with reduced survival. Taken together, there are multiple immune regulatory mechanisms of tumor progression and LILRB4 is an important new actionable target. CA76340 (WZW), KCI TBM program (JBJ) and CCSG P30 CA022453 (GB). Citation Format: Jennifer B. Jacob, Wei-Zen Wei, Benjamin L. Kidder, Tolulope Adeyelu, Andrew Elliott, Gerold Bepler, Joyce D. Reyes. Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu) [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 114.

Abstract 4815: Time to lung cancer treatment in West Virginia and patient survival

Abstract Background: Patients from rural areas typically have poor access to healthcare. Studies have shown varying results on the relationship between time to lung cancer treatment and patient survival. We aimed to examine the association of rurality with timely receipt of lung cancer treatment and survival in West Virginia (WV). Methods: A retrospective study was conducted using WV Cancer Registry data to identify persons diagnosed with NSCLC in WV between 1993 and 2021 who received treatment (surgery, radiation, systemic therapy, other). Participants were classified by rurality (rural vs non-rural), and time to treatment from diagnosis was dichotomized as early treatment (&amp;lt;35 days) or delayed treatment (≥35 days). Descriptive statistics and survival analysis (with univariate and multivariate Cox regression controlling for age, sex, race/ethnicity, marital status, Charlson comorbidity index, cancer stage, and treatment type) were used to address study objectives. Results: Of 10,463 participants, 678 (6.5%) were rural residents. The majority were male (58.1%), married or partnered (59.9%), and non-Hispanic white (97.5%). 61% received early treatment. 45%, 38%, and 16% received systemic therapy, surgery, and radiation, respectively. There were significantly more non-Hispanic white (99.6% vs 97.3%, p&amp;lt;0.004) patients residing in rural areas compared to non-rural areas, and fewer rural residents were diagnosed at stages 1 (29.4% vs 34.3%) or 2 (10.0% vs 11.6%) (p&amp;lt;0.5). Rurality was not associated with time to treatment but was associated with 9% increase in hazard of death (HR=1.09, 95% CI=1.00-1.18, p&amp;lt;0.05). Significant covariates associated with increasing hazard of treatment included being male (HR=1.08, 95% CI=1.04-1.13, p&amp;lt;0.0001) and cancer stage (HR range=1.19-2.38, while being Black and receiving surgery (0.43, 0.30-0.62, p&amp;lt;.0001), radiation (0.48, 0.33-0.68, p&amp;lt;.0001), or systemic therapy (0.33,0.23-0.47, p&amp;lt;.0001) (compared to other treatment) were each associated with reduced hazard of treatment. Significant covariates associated with hazard of death include increasing age (HR=1.01, 95% CI= 1.01-1.02, p&amp;lt;.0001), increasing CCI (HR=1.07, 95% CI=1.05-1.09, p&amp;lt;.0001), being male (HR=1.21, 95% CI=1.16-1.26, p&amp;lt;.0001), increasing cancer stage (HR range=1.58-4.79) while being married (HR=0.92, 95% CI=0.88-0.96, p&amp;lt;.001), receiving surgery (HR=0.16, 95% CI=1.11-0.22, p&amp;lt;.0001), radiation (HR=0.34, 95% CI=0.24-0.49, p&amp;lt;.0001), or systemic treatment (HR=0.17, 95% CI=0.12-0.24, p&amp;lt;.0001), and delayed treatment (HR=0.82, 95% CI=0.78-0.85, p&amp;lt;.0001) were each associated reduced hazard of death. Conclusion: Rurality affects lung cancer outcomes in WV increasing risk of death for NSCLC patients by 9%. Citation Format: Anna R. Lumadue, Sabina O. Nduaguba. Time to lung cancer treatment in West Virginia and patient survival [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 4815.

Abstract 469: PIWI-interacting RNA 50485 (piRNA-50485) is a novel lung tumor suppressor

Abstract Introduction: It is crucial to identify new driver genes and associated downstream pathways to facilitate the development of targeted therapies to effectively treat late-stage and metastatic lung cancer. One pathway involves the Ras association domain family 1 (RASSF1) gene which encodes multiple isoforms. Our laboratory has discovered that the RASSF1C isoform exhibits functional characteristics of an oncogene. We discovered that RASSF1C modulates the expression of PIWI-(Drosophila)-like 1 (PIWIL1, a stem cell renewal gene), as well as novel PIWI-interacting RNAs (piRNAs), which are regulators of the stem cell phenotype and have been linked to oncogenesis. While studying this pathway, we have identified novel piRNAs that are modulated by RASSF1C in non-small cell lung cancer (NSCLC) cells that appear to act as oncogenes or tumor suppressors. Methods: We conducted a global microarray screen to identify RASSF1C PIWI-interacting RNA (piRNA) gene targets. Several piRNA genes that are up- and down-regulated by RASSF1C were identified and the expression of selected up-regulated and down-regulated target genes were confirmed by RT-PCR. We evaluated the impact of selected piRNAs on lung cancer cell proliferation and migration in vitro. We also assessed the expression of the validated piRNA target genes in lung tumor and matched normal tissues. Host and target genes for specific piRNAs were identified using a piRNA database (piRNAdb.org). Results: Among the down-regulated piRNAs, we found that restoring piR-50485 expression drastically decreased lung cancer cell proliferation and invasion, suggesting that piR-50485 could be a potent inhibitor of lung cancer cell growth and progression. Consistent with this, we found that piR-50485 expression is significantly down-regulated in about 60% of human lung cancers. We also identified that the ZHX3 gene (a transcription repressor), which is down-regulated in human lung cancers, is the host gene for piR-50485. In addition, we identified the ZNF618 gene (a transcription co-regulator) that is up-regulated in lung tumor tissue, is a piR-50485 target gene. Consistent with this, treatment of lung cancer cells with piR-50485 mimics resulted in a significant decrease of ZNF618 protein levels, cell proliferation, and migration. Further, increased expression levels of ZHX3 are associated with higher lung cancer patient survival, while increased ZNF618 levels are associated with lower survival. Our novel findings suggest the hypothesis that the piR-50485-ZHX3-ZNF618 gene axis could negatively impact lung cancer cell growth and progression. Conclusion: Exploring the impact of the piR-50485-ZHX3-ZNF618 gene axis on lung cancer growth is a novel concept about which nothing is currently known. We are studying piR-50485 to determine if it can be an effective therapy for lung cancer metastasis, and whether it provides important prognostic information about lung cancer outcomes. Citation Format: Mark E. Reeves, Yousef G. Amaar. PIWI-interacting RNA 50485 (piRNA-50485) is a novel lung tumor suppressor [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 469.

KEAP1-Mutant Lung Cancers Weaken Anti-Tumor Immunity and Promote an M2-like Macrophage Phenotype.

Considerable advances have been made in lung cancer therapies, but there is still an unmet clinical need to improve survival for lung cancer patients. Immunotherapies have improved survival, although only 20-30% of patients respond to these treatments. Interestingly, cancers with mutations in Kelch-like ECH-associated protein 1 (KEAP1), the negative regulator of the nuclear factor erythroid 2-related factor 2 (NRF2) transcription factor, are resistant to immune checkpoint inhibition and correlate with decreased lymphoid cell infiltration. NRF2 is known for promoting an anti-inflammatory phenotype when activated in immune cells, but the study of NRF2 activation in cancer cells has not been adequately assessed. The objective of this study was to determine how lung cancer cells with constitutive NRF2 activity interact with the immune microenvironment to promote cancer progression. To assess, we generated CRISPR-edited mouse lung cancer cell lines by knocking out the KEAP1 or NFE2L2 genes and utilized a publicly available single-cell dataset through the Gene Expression Omnibus to investigate tumor/immune cell interactions. We show here that KEAP1-mutant cancers promote immunosuppression of the tumor microenvironment. Our data suggest KEAP1 deletion is sufficient to alter the secretion of cytokines, increase expression of immune checkpoint markers on cancer cells, and alter recruitment and differential polarization of immunosuppressive macrophages that ultimately lead to T-cell suppression.

Real-World Evidence of the Impact of the COVID-19 Pandemic on Lung Cancer Survival: Canadian Perspective.

Background: The effect of COVID-19 on treatment outcomes in the literature remains limited and is mostly reported either as predictive survival using prioritization and modeling techniques. We aimed to quantify the effect of COVID-19 on lung cancer survival using real-world data collected at the Jewish General Hospital, Montreal. Methods: This is a retrospective chart review study of patients diagnosed between March 2019 and March 2022. We compared three cohorts: pre-COVID-19, and 1st and 2nd year of the pandemic. Results: 417 patients were diagnosed and treated with lung cancer at our centre: 130 in 2019, 103 in 2020 and 184 in 2021. Although the proportion of advanced/metastatic-stage lung cancer remained the same, there was a significant increase in the late-stage presentation during the pandemic. The proportion of M1c (multiple extrathoracic sites) cases in 2020 and 2021 was 57% and 51%, respectively, compared to 31% in 2019 (p < 0.05). Median survival for early stages of lung cancer was similar in the three cohorts. However, patients diagnosed in the M1c stage had a significantly increased risk of death. The 6-month mortality rate was 53% in 2021 compared to 47% in 2020 and 29% in 2019 (p = 0.004). The median survival in this subgroup of patients decreased significantly from 13 months in 2019 to 6 months in 2020 and 5 months in 2021 (p < 0.001). Conclusions: This study is, to our knowledge, the largest single-institution study in Canada looking at lung cancer survival during the COVID-19 pandemic. Our study looks at overall survival in the advanced/metastatic setting of NSCLC during the COVID-19 pandemic. We have previously reported on treatment pattern changes and increased wait times for NSCLC patients during the pandemic. In this study, we report that the advanced/metastatic subgroup had both an increase in the 6-month mortality rate and worsening overall survival during this same time period. Although there was no statistical difference in the proportion of patients with advanced disease, there was a concerning trend of increased M1c disease in cohorts 2 and 3. The higher M1c disease during the COVID-19 pandemic (cohorts 2 and 3) likely played a crucial role in increasing the 6-month mortality rate and leading to a reduced overall survival of lung cancer patients during the pandemic. These findings are more likely to be better identified with longer follow-up.

Cross-validation approaches for penalized Cox regression.

Cross-validation is the most common way of selecting tuning parameters in penalized regression, but its use in penalized Cox regression models has received relatively little attention in the literature. Due to its partial likelihood construction, carrying out cross-validation for Cox models is not straightforward, and there are several potential approaches for implementation. Here, we propose a new approach based on cross-validating the linear predictors of the Cox model and compare it to approaches that have been proposed elsewhere. We show that the proposed approach offers an attractive balance of performance and numerical stability, and illustrate these advantages using simulated data as well as analyzing a high-dimensional study of gene expression and survival in lung cancer patients.