Survival In Non-small Cell Lung Cancer Research Articles

The Incidence and Effect of Different Organ Metastasis on the Prognosis of NSCLC.

The aim of this study was to explore the effect of different organ metastasis on the prognosis of non-small cell lung cancer (NSCLC). Patients with distant metastatic NSCLC were selected from Surveillance, Epidemiology, and End Results database during 2016 to 2019. The incidence of different organ metastasis and their association with clinicopathological factors were explored. Overall survival (OS) and lung cancer-specific survival (LCSS) for metastatic NSCLC were calculated, and multivariate Cox regression analysis was performed with a nomogram for OS being constructed based on Cox regression. Total 26,210 patients with distant metastatic NSCLC were included in this study. Around 48.9% of the metastatic NSCLC were multiple-organ metastasis and bone was the most commonly involved organ (44.4%). For patients with single-organ metastasis, the prognosis for lung or distant lymph nodes (LNs) metastasis was better than others (with median OS of 15 and 16 months for lung and distant LNs metastasis, respectively), and liver metastasis resulted in the worst prognosis with median OS of 8 months. A nomogram was constructed to visualize Cox regression model, along with the receiver operating characteristic (ROC) curve demonstrated good discrimination for the predictive model with 1- and 2-year area under the curve of ROC of 0.687 and 0.702, respectively. The prognosis of NSCLC patients with distant metastasis was poor. Liver metastasis results in the worst prognosis among the single-organ metastasis. The nomogram developed based on the Cox regression model has provided a useful tool to estimate the probability of OS of the metastatic NSCLC.

PTPRD mutation is a prognostic biomarker for sensitivity to ICIs treatment in advanced non-small cell lung cancer.

Immune checkpoint inhibitors (ICIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC). ICIs can provide durable responses and prolong survival for some patients. With the increasing routine of next-generation sequencing (NGS) in clinical practice, it is essential to integrate prognostic factors to establish novel nomograms to improve clinical prediction ability in NSCLC with ICIs treatment. Clinical information, response data, and genome data of advanced NSCLC treated ICIs were obtained from cBioPortal. The top 20 gene alterations in durable clinical benefit (DCB) were compared with those genes in no durable benefit (NDB). Survival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram. The mutation of PTPRD was significantly related to progression free survival (PFS) and overall survival (OS) in advanced NSCLC with ICIs treatment (PFS: p = 0.0441, OS: p = 0.0086). The PTPRD mutation was closely related to tumor mutational burden (TMB) and tumor-infiltrating immune cells (TIICs). Two novel nomograms were built to predict the PFS and OS of advanced NSCLC patients with ICIs treatment. Our study suggested that PTPRD mutations could serve as a predictive biomarker for the sensitivity to ICIs treatment and PFS and OS in advanced NSCLC with ICIs. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS for advanced NSCLC patients with ICIs.

Radiomics-Clinical AI Model with Probability Weighted Strategy for Prognosis Prediction in Non-Small Cell Lung Cancer.

In this study, we propose a radiomics clinical probability-weighted model for the prediction of prognosis for non-small cell lung cancer (NSCLC). The model combines radiomics features extracted from radiotherapy (RT) planning images with clinical factors such as age, gender, histology, and tumor stage. CT images with radiotherapy structures of 422 NSCLC patients were retrieved from The Cancer Imaging Archive (TCIA). Radiomic features were extracted from gross tumor volumes (GTVs). Five machine learning algorithms, namely decision trees (DT), random forests (RF), extreme boost (EB), support vector machine (SVM) and generalized linear model (GLM) were optimized by a voted ensemble machine learning (VEML) model. A probabilistic weighted approach is used to incorporate the uncertainty associated with both radiomic and clinical features and to generate a probabilistic risk score for each patient. The performance of the model is evaluated using a receiver operating characteristic (ROC). The Radiomic model, clinical factor model, and combined radiomic clinical probability-weighted model demonstrated good performance in predicting NSCLC survival with AUC of 0.941, 0.856 and 0.949, respectively. The combined radiomics clinical probability-weighted enhanced model achieved significantly better performance than the radiomic model in 1-year survival prediction (chi-square test, p < 0.05). The proposed model has the potential to improve NSCLC prognosis and facilitate personalized treatment decisions.

Clinicopathological and prognostic significance of SMAD4 in non-small cell lung cancer: A meta-analysis and database validation.

The relationship between SMAD family member 4 (SMAD4) and the clinicopathological and prognostic significance of non-small cell lung cancer (NSCLC) patients is unclear. Our aim was to investigate the association between SMAD4 expression and clinicopathological parameters and NSCLC prognosis. We searched articles in databases from inception to July 2022 to retrieve literature related to SMAD4 expression and the clinicopathological and/or prognostic significance of NSCLC patients. Odds ratios (ORs), hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. We evaluated the expression of SMAD4 and overall survival (OS) in NSCLC using the Kaplan-Meier plotter database. Eight articles with 1461 NSCLC patients were included. SMAD4 expression was related to tumor differentiation (OR = 0.359, 95% CI: 0.238-0.543, P = .000), lymph node metastasis (OR = 0.469, 95% CI: 0.04-0.725, P = .001), tumor node metastasis stage (OR = 0.238, 95% CI: 0.156-0.362, P = .000) and good OS (HR = 0.592, 95% CI: 0.332-0.853, P = .000) in NSCLC. There was no significant association between SMAD4 expression and age (OR = 0.822, 95% CI: 0.515-1.312, P = .411) or sex (OR = 1.056, 95% CI: 0.675-1.653, P = .811). Furthermore, SMAD4 expression was lower in NSCLC, and a good prognosis in NSCLC (HR = 0.6, 95% CI = 0.51-0.72, P = 4.2 e-9) was shown to correlate with higher SMAD4 expression using the Kaplan-Meier Plotter database. SMAD4 expression is lower in NSCLC and correlated with lymph node metastasis, tumor differentiation, tumor node metastasis stage and good OS for NSCLC patients.

LncRNA NBR2 Regulates Cancer Cell Stemness and Predicts Survival in Non-small Cell Cancer Patients by Downregulating TGF-β1.

LncRNA NBR2 is a key regulator in cancer metabolism. However, its role in lung cancer is unknown. This study aimed to explore the function of NBR2 in non-small cell lung cancer (NSCLC), which is the most common type of lung cancer. Paired NSCLC and non-cancer tissues were collected from 68 patients with NSCLC. The expression of NBR2 and transforming growth factor-β1 (TGF-β1) in these samples was analyzed by RT-qPCR. The prognostic value of NBR2 for NSCLC was explored by performing a 5-year follow-up study. The interaction between NBR2 and TGF-β1 in two NSCLC cell lines was detected by overexpression assay, followed by RT-qPCR and Western blot analysis. Flow cytometry was performed to evaluate the role of NBR2 and TGF-β1 in regulating NSCLC cell stemness. NBR2 was significantly downregulated in NSCLC tissues than that in non-cancer tissues of NSCLC patients, and low expression levels of NBR2 predicted poor survival. TGF-β1 was significantly upregulated in NSCLC tissues than that in non-cancer tissues, and was inversely correlated with NBR2. Overexpression of NBR2 downregulated TGF-β1, while overexpression of TGF-β1 did not affect the expression of NBR2. Overexpression of NBR2 inhibited, while overexpression of TGF-β1 promoted NSCLC cell stemness. Overexpression of TGF-β1 attenuated the effects of overexpression of NBR2. Mechanically, NBR2 interacted with Notch1 protein to inhibit its expression, thereby inhibiting the expression of TGF-β1 and further affecting the proportion of CD133+ cells. LncRNA NBR2 regulates cancer cell stemness and predicts survival in NSCLC possibly by downregulating TGF-β1 through Notch1.

Impact of diabetes on stage I lung cancer treatment patterns and prognosis in older adults: A population-based cohort study

BackgroundDiabetes is a common comorbidity in patients with early-stage non-small cell lung cancer (NSCLC), a growing population due to increased LC screening. However, it is unknown if diabetes is associated with less aggressive NSCLC treatment and worse NSCLC outcomes. This study aimed to investigate treatment patterns and outcomes of older patients with Stage I NSCLC and diabetes. MethodsUsing national cancer registry data linked to Medicare, we identified patients ≥65 years old with Stage I NSCLC. Patients were categorized as having no diabetes, diabetes without severe complications (DM-c), or diabetes with ≥1 severe complication (DM + c). We used multinomial logistic regression to assess the association of diabetes and NSCLC treatment. The association of diabetes category with NSCLC and non-NSCLC survival was analyzed with Fine-Grey competing-risks regression. ResultsIn 25,358 patients (75% no diabetes, 12% DM-c and 13% had DM + c), adjusted analyses showed that DM-c and DM + c were associated with increased odds of receiving limited resection rather than lobectomy (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.07–1.37 and OR 1.42, 95% CI 1.26–1.59, respectively). Competing risk regression showed diabetes was associated with increased risk of non-NSCLC death (DM-c hazard ratio [HR] 1.16, 95% CI: 1.08–1.25, DM + c HR 1.49, 95% CI: 1.40–1.59), but not NSCLC-specific death. ConclusionThis study uncovers critical information on how diabetes is associated with less aggressive early-stage NSCLC care in older patients. This study also confirms that diabetes increases death from non-lung cancer causes and managing comorbidities is crucial to improving outcomes in older early-stage NSCLC survivors.

Dexamethasone induces cancer mitigation and irreversible senescence in lung cancer cells via damaging cortical actin and sustained hyperphosphorylation of pRb

Activation of the glucocorticoid receptors by its cognate ligand, dexamethasone (DEX) is commonly used as an adjuvant treatment in solid tumors. However, its direct effect on cancerous phenotype is not fully understood. We explored the effect and molecular mechanisms of DEX action in lung cancer. In in vitro experiments, DEX treatment causes decrease in migration, invasion and colony formation ability of A549 cells even at lower doses. DEX also decreased adhesion of A549 cells by reducing the formation of cortical actin. Treatment with RU486, a GR antagonist, indicated that these effects are partially mediated through GR. Further; DEX induces G0/G1 arrest of A549 cells. Mechanistically, DEX induces expression of both CDK inhibitors (p21Cip1, p27Kip1) and cyclin-dependent kinases (CDK4, CDK6). Due to this compensatory activation of CDKs and CDKIs, DEX induces the hyper phosphorylation state of Rb protein (pRb) leading to irreversible senescence as confirmed by β-gal staining. Next, in clinical dataset of NSCLC (Non-small cell lung cancer), GR was lowly expressed in cancer patients as compared to the normal group, where higher expression of GR led to higher overall survival of NSCLC indicating for a protective role of GR. Interestingly, when combined with chemotherapeutic agents, DEX can modulate the drug-sensitivity of cells. Taken together, these data indicate that DEX through GR activation may suppress tumor growth by decreasing proliferation and inducing irreversible senescence and combination of standard chemotherapy and DEX can be a potential treatment for NSCLC.

Prognostic Factors of Chemotherapy Response and Survival in Non-Small Cell Lung Cancer: Data from Real-World Practice with Limited Access to Novel Therapy

Background: Chemotherapy is a backbone treatment in advanced-stage non-small cell lung cancer (NSCLC) for non-targetable mutations and inaccessible to novel therapies. However, the data on the response rate, factors of chemotherapy response, and survival in Thailand are limited. Objective: To find the chemotherapy response rate, factors that predict chemotherapy response and survival in advanced-stage NSCLC. Materials and Methods: A retrospective cohort study was performed by including advanced-stage NSCLC patients older than 18 years old who received chemotherapy at the medical oncology unit, Sawanpracharak Hospital between July 2014 and January 2020. Demographic data, laboratory data, details of treatment, computed tomography (CT) of chest, and survival time were collected. Descriptive statistical analyses followed by univariable and multivariable were performed to determine factors associated with chemotherapy response. Kaplan-Meier survival curve was used to estimate overall survival (OS), and the log-rank test was performed to compare survival differences in each group. The univariable and multivariable Cox regression method was adopted for OS. Results: Tree hundred four chemotherapy-treated advanced-stage NSCLC were included. The chemotherapy response rate was 45.5%, and ECOG 0-1 was a favorable prognosis for chemotherapy response (OR 3.03, 95% CI 1.480 to 7.370, p=0.004). Pericardial metastasis (HR 1.833, 95% CI 1.102 to 3.215, p=0.021), liver metastasis (HR 2.05, 95% CI 1.131 to 3.201, p=0.002), non-objective response rate (ORR) for chemotherapy (HR 1.429, 95% CI 1.099 to 1.859, p=0.008) were worse prognosis factors. Obtaining second-line and third-line systemic treatment were favorable prognoses of survival in advanced-stage NSCLC (HR 0.476, 95% CI 0.348 to 0.651, p&lt;0.001 and HR 0.247, 95% CI 0.123 to 0.494, p&lt;0.001, respectively). Conclusion: The response rate in chemotherapy-treated advanced-stage NSCLC was 45.5%. ECOG 0-1 was an independent factor in chemotherapy response. Liver metastasis, pericardial metastasis, no subsequent treatment, and poor response to chemotherapy were worse prognosis outcomes in advanced-stage NSCLC. Keywords: NSCLC; Advanced-stage; Factor of chemotherapy response; Factor of survival

Fate and Efficacy of Engineered Allogeneic Stem Cells Targeting Cell Death and Proliferation Pathways in Primary and Brain Metastatic Lung Cancer.

Primary and metastatic lung cancer is a leading cause of cancer-related death and novel therapies are urgently needed. Epidermal growth factor receptor (EGFR) and death receptor (DR) 4/5 are both highly expressed in primary and metastatic non-small cell lung cancer (NSCLC); however, targeting these receptors individually has demonstrated limited therapeutic benefit in patients. In this study, we created and characterized diagnostic and therapeutic stem cells (SC), expressing EGFR-targeted nanobody (EV) fused to the extracellular domain of death DR4/5 ligand (DRL) (EVDRL) that simultaneously targets EGFR and DR4/5, in primary and metastatic NSCLC tumor models. We show that EVDRL targets both cell surface receptors, and induces caspase-mediated apoptosis in a broad spectrum of NSCLC cell lines. Utilizing real-time dual imaging and correlative immunohistochemistry, we show that allogeneic SCs home to tumors and when engineered to express EVDRL, alleviate tumor burden and significantly increase survival in primary and brain metastatic NSCLC. This study reports mechanistic insights into simultaneous targeting of EGFR- and DR4/5 in lung tumors and presents a promising approach for translation into the clinical setting.

Sociodemographic factors affecting survival in stage IIIA NSCLC treated with surgery-based treatment or definitive chemoradiation with immunotherapy consolidation: An NCDB analysis.

e18555 Background: Stage IIIA non-small cell lung cancer (NSCLC) is a heterogeneous disease treated by surgery-based approach or definitive chemoradiation (CRT) and immunotherapy (ICI) consolidation. Studies have shown that black patients in general are diagnosed at advanced stages, are less likely to receive ICI, and have lower overall survival (OS) compared to whites. Importantly, ICI was shown to impart similar or even better OS among advanced-stage black NSCLC patients, compared to whites. Geographical location and socioeconomic status have also been shown to affect outcomes. There are no studies on sociodemographic factors affecting survival in stage IIIA NSCLC in the ICI era. Methods: We used National Cancer Database (NCDB) to identify 23,110 patients with clinical stage IIIA NSCLC treated with either surgery-based approach or definitive CRT followed by ICI during 2017-2019, and surgery-based treatment or CRT during 2014-2016. We analyzed age, race, sex, insurance type, income, geographic location, Charlson Comorbidity Index (CCI) and education. Kaplan-Meier (KM) plots were used to examine survival curves and descriptive analysis was performed to examine the characteristics of sociodemographic variables by the two treatment modalities. Cox regression analysis was used to identify factors associated with OS. Results: ICI maintenance improved the OS of all stage IIIA NSCLC patients after CRT during 2017-2019 compared to CRT only in 2014-2016. On multivariate analysis of surgical and CRT-ICI cohorts, blacks had slightly better OS compared to whites (HR, 95%CI, p-value) (0.89, 0.84-0.95, &lt; 0.001) but lower than other races including Asians (0.77, 0.69-0.87, &lt; 0.001). While there was no OS difference in the surgical arm (0.94, 0.83-1.07, p = 0.356) between black and white patients, better survival was seen in blacks in the CRT-ICI arm (0.88, 0.82-0.94, &lt; 0.001). No significant interaction between race and CRT-ICI was identified which indicates the benefit of CRT-ICI is independent of the race effect. Other factors associated with lower OS were older age with age &gt; 75 HR 1.00, ages 19-39 (0.47, 0.35-0.64) ages 40-64 (0.71, 0.67-0.75), ages 65-74 (0.79, 0.76-0.83), median quartile income &lt; $40,227 (1.07, 1.01-1.14), non-metro location (1.12, 1.07-1.17), non-academic facility (1.09, 1.05-1.14), and male sex (1.24, 1.20-1.29). Insurance status had no effect on OS. Conclusions: Our study indicates that there is no survival difference between white and black patients treated with surgery, but blacks had better survival when treated with CRT-ICI. Racial disparity in NSCLC survival depends on stage and access to care. Treatment modality, income, metro location, and access to an academic center are more significant predictors of survival than race. Interestingly, health insurance had no impact on OS.

Optimal number of lymph node stations associated with improved survival among patients with non-small cell lung cancer (NSCLC).

8571 Background: Good quality pathologic nodal evaluation is associated with improved long-term survival in NSCLC after surgical resection. However, there is no universal definition of quality. We examined the association between number of lymph node stations (NLNS) sampled and overall survival. Methods: We examined the population-based Mid-South Quality of Surgical Resection (MS-QSR) cohort, excluding patients with neoadjuvant therapy, positive margins, and secondary resections. We summarized demographic and clinical characteristics with appropriate statistics. We employed four Cox regression models: 1) including NLNS as the only predictor; 2) model 1, adjusting for age, sex, histology, clinical stage, extent of resection, and surgical technique; 3) examined the impact of pathologic staging (pStage in 3 groups: IA/IB[&lt;4cm tumor size]; IB[&gt;4cm]/II/IIIA[pN2-]; pN2]) by modeling interaction with pStage and NLNS; 4) model 3 plus adjustments (no clinical stage). In a cut point analysis to identify the optimal NLNS for improved survival, we dichotomized the NLNS for cut points 0 to 12. Hazard ratios (HR) were calculated (as above) and plotted for each dichotomization. Results: The 3916 eligible patients were 21% Black, 54% male, 15% on Medicaid and 49% Medicare; 84% and 85% had clinical and pathologic stage I/II, respectively; 84% had no invasive staging; 84% had a PET-CT scan. For every additional lymph node station sampled, the HR decreased by 0.94 (95% confidence interval: 0.92, 0.96). After adjustments, the HR remained significant (Table). Our pStage cohorts comprised of 2474 (64%) IA/IB[&lt;4cm]; 1080 (28%) IB[&gt;4cm]/II/IIIA[pN2-]; and 290 (8%) pN2+. Once stratified, HRs remained significant among those with early stage but not for pN2+ (Table). When further adjusted, only pStage IA/IB[&lt;4cm] patients had a significant HR, 0.94 (0.91, 0.97). The cut point analysis indicated sequential survival improvement up to ≥ 7 total stations sampled, consistently across all models/adjustments. Conclusions: The number of lymph node stations examined is directly associated with survival after lung cancer resection. Examination of a total of 7 intrapulmonary, hilar and mediastinal stations seems optimal. Hazard ratios (95% confidence intervals) for modeling hazards as a function of lymph node stations sampled (model 1), further adjusted for age, sex, histology, clinical stage, extent of resection, and surgical technique (model 2), including interaction with pathologic stage with no adjustments (model 3), and interaction with pathological stage with adjustments (no clinical stage) (model 4). [Table: see text]

Stimulator of interferon gene (STING) expression as a biomarker for overall survival in PDL1-negative, TMB-low non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs).

9120 Background: cGAS-STING (CGS) is an intracellular DNA sensing pathway that when activated, stimulates interferon and other immune-related signaling pathways. While increased expression of CGS-related genes has been associated with better survival in NSCLC, studies investigating this phenomenon in tumors less likely to respond to ICIs such as PDL1-negative, TMB-Low NSCLC are lacking. Here we report the role of CGS pathway in NSCLC tumors that are both PDL1-negative and TMB-Low. Methods: DNA (592-gene or whole exome) and RNA sequencing (whole transcriptome) was performed for NSCLC specimens (n=7264) submitted to Caris Life Sciences (Phoenix, AZ). PDL1 negativity was defined as &lt;1% TPS score (22C3) &amp; TMB-Low as &lt;10 mutations/Mb. Hierarchical Agglomerative Clustering (HAC) was performed on STING pathway genes (CXCL10, CCL5 and GZB) and tumors were grouped into STING-high (n=3070), STING-intermediate (n=1609) and STING-low (n=2585) groups. Microenvironmental cell populations (MCP)-counter analysis was used to estimate cellular composition of immune cells. Statistical significance was determined using chi-square/Fisher’s exact/Mann-Whitney U tests and adjusted for multiple comparisons (q&lt;0.05). Kaplan Meier method was used to estimate the overall survival (OS) derived from insurance claims of IO treated pts with NSCLC (n=400). Pts were stratified into groups above or below the median expression of the STING gene ( TMEM173). Results: Compared to STING-low, tumors that were STING-high had enrichment in immune cell infiltrates including CD8+ T cells (4.4-fold) and B-cells (5.9-fold); Additionally, STING-high cohort had significantly higher expression of immune checkpoint (IC) genes including CD274(2.5-fold), CD80 (2.7-fold, all q&lt;0.05). STING-high tumors also had a higher prevalence of TP53 mutations (mts) and a lower prevalence of STK11 and KEAP1 mts (Table). Median overall survival (OS) was 21.1 months in the STING-high cohort (n=200) vs 11.9 months in the STING-low cohort (n=199) in IO treated pts (HR = 0.62, p&lt;0.000.1) Conclusions: To our knowledge this is the largest real-world dataset indicating that enrichment of both the STING gene, and gene signatures associated with the STING pathway represent valuable transcriptomic biomarkers to stratify pts with PDL1-negative and TMB-Low NSCLC who benefit more from IO therapies. Conversely, novel IO combination strategies need to be employed in STING-low tumors to enhance outcomes. [Table: see text]

Outcome analysis of immunotherapy and possible prognostic role of pretreatment neutrophil-lymphocyte ratio in lung cancer: An Appalachian study.

e21053 Background: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of lung cancer resulting in better survival benefits. We are reporting outcome analysis of lung cancer patients treated with ICI in our institution. Methods: We performed retrospective chart review of lung cancer patients treated with ICI at our institution between June 2016 and March 2022. Results: A total of 289 patients were identified- 241 had non-small cell lung cancer (NSCLC) and 48 had small cell lung cancer (SCLC). A total of 109 patients (37.7%) developed immunotherapy related adverse events (IRAE): 92 (38.1%) with NSCLC and 17 (35.4%) with SCLC. Average time to develop IRAE was 3 months in both NSCLC and SCLC. IRAE grades 1,2,3,4 were noted in 33%, 20%, 15%, 31% patients respectively. 34 of 63 (53%) patients who received Ipilimumab-Nivolumab developed more IRAE than any other ICI with fatigue and dermatitis being the most common IRAE associated with this ICI. 79 of 183 (43%) patients who received RT developed IRAE (p = 0.012). Median overall survival (OS) for NSCLC was 35 months, 41 months, 27 months, 15 months for stages 1,2,3,4, respectively (p = 0.03). Median OS for extensive stage SCLC was 14.6 months. Median OS for NSCLC with and without IRAE was 30 and 23 months, respectively (p = 0.02). Median OS for SCLC with and without IRAE was 16.7 and 16.2 months, respectively (p = 0.5). Median OS for NSCLC when steroids were used to treat IRAE was 25 months, and 63 months if no steroids were used (p = 0.027). Better median overall survival rate was noted in patients with low Neutrophil-Lymphocyte ratio (defined as NLR &lt; 5) 29.23 months vs 20.59 months (high NLR) (p = 0.019). Although demographics like male sex, smoking history, higher BMI and poor ECOG performance status had numerically increased the risk of developing IRAE, no statistical significance was noted. Conclusions: Overall results of our analysis are mostly consistent with the current literature on survival rates in Lung Cancer. IRAE may have a predictive role in survival, as we observed that patients with NSCLC developing IRAE had better survival rates. Ipilimumab-Nivolumab combination resulted in more IRAE than any other ICI. Pneumonitis was the most common IRAE among all patients receiving ICI. Also, Radiation-therapy increased the risk of developing IRAE. Our observation that steroid use in treating IRAE was associated with lower survival is concerning. This may be due to higher grade IRAE/toxicities and possible decreased ICI effectiveness. Regardless of IRAE, low pretreatment NLR resulted in better survival rates. The role of pretreatment NLR as a potential prognostic tool to assess survival outcomes requires validation in a randomized clinical trial.

Multi-center real-world data curation and assessment of tumor growth rate and overall survival in advanced NSCLC treated with PD-(L)1 immune checkpoint inhibitor therapy.

9124 Background: While Immune Checkpoint Inhibitors (ICI) have become the standard-of-care for advanced non-small cell lung cancer (NSCLC) for certain patient populations, durable responses only occur in a small subset of patients. Therefore, there is an unmet need to identify patients that will respond before and during treatment to optimize treatment strategies. Multiple studies have shown promise that quantitative imaging biomarkers can predict response to ICI therapy. Studies have also shown that tumor growth parameters derived from time series data can provide early indications of long-term response. However, most studies to date have investigated single institution or clinical trial datasets, which are inadequate to capture the broad spectrum of real-world diversity of ICI treatments. In this study, we aimed to build a generalizable, well-validated imaging biomarker for treatment response. Methods: We have curated a retrospective dataset including serial imaging data of 1,215 advanced NSCLC patients who received ICIs from nine institutions across the US and Europe, capturing the diversity of the imaging data, such as CT scanner models, image acquisition parameters, reconstruction algorithms, as well as diversity in patient population, performance status, and treatment settings. Expert lesion annotations and manual volumetric segmentations were performed on all visible lesions (ranging from 1-18 lesions per subject, totaling 6,441 lesions) across the serial imaging data (ranging from 1-18 follow-up scans per subject), which enables lesion and organ-specific tumor burden assessment. We stratified overall survival based on volumetric response and tumor growth rate using a model defined by the sum of exponential growth ( g) and decay ( d), vol(t) = vol(0)*(egt + e-dt -1). Results: Survival analysis showed that the 3-month volumetric response (N = 875) was significantly associated with overall survival (OS) for the lowest quartile (Q1; log-rank p-value, P = 2.1e-4) and highest quartile (Q4; P = 9.8e-8) compared to the middle quartiles (Q2+Q3). The median overall survival (OS) stratified by the volumetric response was 547.7, 450.9, and 332.0 days in the Q1, Q2+Q3, Q4 quadrants, respectively. Among patients having a minimum of 2 follow-up scans in the first 18 weeks (N = 264), we found that patients with the tumor growth parameter ( g) in the highest quartile had significantly lower OS compared to the patients in the Q2+Q3 quadrants (P = 7.2e-5). Conclusions: Our results demonstrate the potential of large multi-center real-world imaging datasets in investigating novel early response assessment methodologies, such as volumetric tumor burden quantification and tumor growth modeling. In our further work, we will investigate response patterns at individual lesion levels and correlations with overall patient-level response.

The association of race and curative-intent treatment with mortality outcomes among early-stage NSCLC.

e20563 Background: Racial disparities in early-stage non-small cell lung cancer (NSCLC) survival have persisted between blacks and whites in the past few decades. The role of receipt of curative-intent surgery and/or stereotactic body radiation therapy (SBRT) in this disparity is unclear. We examined the associations of race/ethnicity and curative-intent treatment (surgery and/or SRBT) with mortality outcomes among early-stage NSCLC patients, using population-based data from Florida, the third largest state in the US and the second state in the number of cancer cases diagnosed annually. Methods: Florida Cancer Data System (FCDS) data were used to estimate cancer-specific mortality for all patients diagnosed in the state between 2007 to 2018 for each racial/ethnic group: non-Hispanic black (NHB), Hispanic, and Asian/Pacific Islander (API)) and non-Hispanic whites (NHW). FCDS were further individually linked to population-based discharge data (94% match rate) containing patient-level comorbidities and treatment-specific information. Multivariable Cox proportional hazards regression models were applied to study the association of race/ethnicity and curative-intent treatment with lung cancer-specific mortality (LCSM). Competing risk analysis (deaths by other causes) for LCSM was performed. Results: We identified 63,872 early-stage NSCLC patients; 83.2% NHW, 6.6% NHB, 8.7% Hispanic, 0.77% API, and 0.79% other races; 72.2% of patients received curative-intent treatment (surgery and/or SRBT). The median lung cancer-specific survival time for all patients was 5.43 years (95% CI, 5.30-5.56). After inclusion of all clinical and sociodemographic factors including stage at diagnosis and comorbidities, race/ethnicity (NHB vs NHW: hazard ratio [HR], 1.06; 95% CI, 1.00-1.11) and curative-intent treatment (SBRT vs curative-intent surgery: HR, 1.87; 95% CI, 1.78-1.97;) were both independently associated with LCSM. Nevertheless, after combining the effect of race/ethnicity and curative-intent treatment in the same fully adjusted model, NHB patients who received curative-intent treatment experienced nearly identical survival as their NHW counterparts (HR, 0.95; 95% CI, 0.87-1.03). Similar findings were observed in competing risk analysis (subdistribution hazard ratio [sHR], 0.97; 95% CI: 0.89-1.02). Conclusions: In this racially diverse population, receipt of curative-intent treatment revealed comparable survival between NHB and NHW patients. The results underscore the importance of considering receipt of (specifically) curative-intent treatment rather than receipt of any form of surgery or radiotherapy in racial/ethnic survival disparities. The uptake of curative-intent surgery and SBRT, which currently stands at 56.5% and 9.4% respectively, should be increased to improve survival outcomes for early-stage NSCLC for all.

Survival impact of fibrotic interstitial lung abnormalities in resected stage IA non-small cell lung cancer.

To assess the association between fibrotic interstitial lung abnormalities (ILAs) and long-term survival in patients with resected Stage IA non-small cell lung cancer (NSCLC). Data of patients who underwent curative resection of pathological Stage IA NSCLC between 2010 and 2015 were retrospectively analysed. ILAs were evaluated using pre-operative high-resolution CT scans. The association between ILAs and cause-specific mortality was assessed via Kaplan-Meier analysis and the log-rank test. Cox proportional hazards regression was performed to determine the risk factors for cause-specific death. Overall, 228 patients were identified (63.27 ± 8.54 years, 133 men [58.3%]). ILAs were detected in 24 patients (10.53%). Fibrotic ILAs were observed in 16 patients (7.02%), and there was a significantly higher cause-specific mortality rate among patients with fibrotic ILAs compared with patients with no ILAs (p < 0.001). Patients with fibrotic ILAs had a significantly higher cause-specific mortality rate than patients without ILAs at 5 post-operative years (survival rate: 61.88% vs 93.03%, p < 0.001). The presence of afibrotic ILA was an independent risk factor for cause-specific death (adjusted hazard ratio = 3.22; 95% confidence interval: 1.10, 9.44; p = 0.033). The presence of afibrotic ILA was a risk factor for cause-specific death in patients with resected Stage IA NSCLC. Radiologists and clinicians should be familiar with the relatively new concept of ILAs and understand the close association between ILA status and long-term survival in resected Stage IA NSCLC. Patients presenting fibrotic ILAs should receive appropriate surveillance and management to optimise prognosis. Fibrotic ILAs are important findings implicated inthe long-term survival of patients with resected Stage IA NSCLC. Specific management is required for this group.

The role of miR-143-3p/FNDC1 axis on the progression of non-small cell lung cancer.

The study aimed to explore the functional role of fibronectin type III domain containing 1 (FNDC1) in nonsmall cell lung cancer (NSCLC), as well as the mechanism governing its expression. The expression levels ofFNDC1 and related genes in tissue and cell samples were detected by qRT-PCR. Kaplan-Meier analysis was employed to analyze the association between FNDC1 level and the overall survival of NSCLC patients.Functional experiments such as CCK-8 proliferation, colony formation, EDU staining, migration and invasion assays were conducted to investigate the functional role of FNDC1 in regulating the malignancy of NSCLCcells. Bioinformatic tools and dual-luciferase reporter assay were used to identify the miRNA regulator of FNDC1 in NSCLC cells. Our data revealed the upregulation of FNDC1 at mRNA and protein levels in NSCLCtumor tissues cancer cell lines, compared with normal counterparts. NSCLC patients with higher FNDC1 expression suffered from a poorer overall survival. FNDC1 knockdown significantly suppressed the proliferation,migration and invasion of NSCLC cells, and had an inhibitory effect on tube formation. We further demonstrated that miR-143-3p was an upstream regulator of FNDC1 and miR-143-3p expression was repressed inNSCLC samples. Similar to FNDC1 knockdown, miR-143-3p overexpression inhibited the growth, migration and invasion of NSCLC cells. FNDC1 overexpression could partially rescue the effect of miR-143-3p overexpression. FNDC1 silencing also suppressed the tumorigenesis of NSCLC cells in mouse model. In conclusion,FNDC1 promotes the malignant prototypes of NSCLC cells. miR-143-3p is a negative regulator of FNDC1 in NSCLC cells, which may serve as a promising therapeutic target in NSCLC.

Cost-effectiveness of cemiplimab plus chemotherapy versus chemotherapy for the treatment of advanced non-small cell lung cancer.

In patients with advanced non-small cell lung cancer (aNSCLC), cemiplimab plus chemotherapy prolonged overall survival (OS) and progression-free survival (PFS) significantly compared to chemotherapy alone. The cost-effectiveness of these drugs is still uncertain. The aim of this study is to assess the cost-effectiveness of cemiplimab plus chemotherapy compared with chemotherapy for the treatment of aNSCLC from the third-party payer perspective in the United States. The cost-effectiveness of cemiplimab with chemotherapy versus chemotherapy for the treatment of aNSCLC was evaluated using a partitioned survival model containing three mutually incompatible health states. The clinical characteristics and outcomes used in the model were gathered from EMPOWER-Lung 3 trial. We have conducted deterministic one-way sensitivity analysis and probabilistic sensitivity analysis in order to evaluate the robustness of the model. The primary outcomes considered were the costs, life-years, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratio (ICER), incremental net health benefits (INHB), and incremental net monetary benefits (INMB). Treatment of aNSCLC with cemiplimab plus chemotherapy increased efficacy by 0.237 QALYs and was associated with an increased total cost of $50,796 compared to chemotherapy alone, resulting in an ICER of $214,256/QALY gained. At a WTP threshold of $150,000/QALY, the INHB of cemiplimab plus chemotherapy was 0.203 QALYs and the INMB was $304,704 compared to chemotherapy alone. The probabilistic sensitivity analysis revealed that there was only a 0.04% chance that cemiplimab with chemotherapy would be cost-effective at a WTP threshold of $150,000/QALY. The performance of model was mainly determined by the price of cemiplimab, according to a one-way sensitivity analysis. From the third-party payer perspective, cemiplimab combined chemotherapy is unlikely to be a cost-effective option for the treatment of aNSCLC at the WTP threshold of $150,000/QALY in the United States.

Abstract 3936: ALK fusion oncogene driven SERPINB4 expression enhances tumor survival in NSCLC

Abstract Anaplastic lymphoma kinase (ALK) fusion variants in non-small-cell-lung cancer (NSCLC) consist of numerous dimerising fusion partners, with the most common being EML4. Clinical data suggests that the degree of treatment benefit in response to ALK tyrosine kinase inhibitors (TKIs) differs among the variant present in the patient tumor. Therefore, a better understanding the oncogenic signaling networks driven by different ALK-fusion variants is important. Here, we developed highly controlled doxycycline-inducible cell models bearing four different ALK fusion proteins, namely EML4-ALK-V1, EML4-ALK-V3, KIF5B-ALK, and TFG-ALK, in the context of non-tumorigenic NL20 human bronchial epithelial cells. These were complimented by patient-derived NSCLC cell lines harboring either EML4-ALK-V1 or EML4-ALK-V3 fusions. RNA-seq and phosphoproteomics analysis were employed to identify dysregulated genes and hyper/hypo-phosphorylated proteins associated with ALK fusion expression. Among ALK fusion induced responses, we noted a robust inflammatory signature that included up-regulation of the Serpin B4 serine protease inhibitor in both NL20-inducible cell models and ALK-positive NSCLC patient-derived cell lines. We show that STAT3 is a major transcriptional regulator of SERPINB4 downstream of ALK fusions, along with NF-kB and AP1. The upregulation of SERPINB4 promotes survival of ALK fusion expressing cells and inhibits natural killer (NK) cell-mediated cytotoxicity. In conclusion, our study reveals a novel ALK downstream survival axis that regulates Serpin B4 expression and identifies a molecular target that has potential for therapeutic impact targeting the immune response together with ALK TKIs in NSCLC. Citation Format: Tzu-Po Chuang, Wei-Yun Lai, Jonatan L. Gabre, Dan E. Lind, Ganesh Umapathy, Abdulmalik A. Bokhari, Bengt Bergman, Linnea Kristenson, Fredrik B. Thorén, Anh Le, Robert Doebele, Jimmy V. Eynden, Ruth H. Palmer, Bengt Hallberg. ALK fusion oncogene driven SERPINB4 expression enhances tumor survival in NSCLC. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3936.

Abstract 5373: Autoencoder-based multimodal prediction of survival for non-small cell lung cancer

Abstract Most non-small cell lung cancer (NSCLC) prognosis prediction approaches use one data type and do not take advantage of the large amount of multimodal data available. To evaluate and explore the benefits of multimodal data integration, we present a combined feature selection and denoising autoencoder pipeline for NSCLC survival prediction and survival subtype identification using microRNA (miRNA), mRNA, DNA methylation, long non-coding RNA (lncRNA) and clinical data. Survival performance for both lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) patients was compared across modality combinations, data integration time and training data types. Multimodal data combinations outperformed single data modalities, with the early integration of all data modalities achieving concordance indexes (C-indexes) of 0.67 (±.04) and 0.63 (±.02) for LUAD and LUSC, respectively versus corresponding C-index of 0.64 (±.02) and 0.59 (±.03) for the best single cell modality (clinical). Notably, combining just lncRNA and clinical data facilitated effective survival discrimination, with C-indexes of 0.69 (±.03) for LUAD and 0.62 (±.03) for LUSC. Overall, higher performance was achieved by using a single denoising autoencoder for all biological data (early integration) and by training on both LUSC and LUAD patient data together. Two survival subtypes (log rank test p-value=1e-9) were identified, with 991 differentially expressed transcripts in the poorer survival group. Our analysis shows the value of multimodal data integration for predicting NSCLC progression, with especially good performance using the combination of lncRNA and clinical data. Early integration of biological data, with an initial linear feature selection technique and a denoising autoencoder for dimensionality reduction, showed effective survival performance and survival subtype identification. Further research is underway to expand analysis to different cancer types and data modalities and extract more biological interpretability from autoencoder models. Citation Format: Jacob G. Ellen, Etai Jacob, Nikos Nikolaou, Natasha Markuzon. Autoencoder-based multimodal prediction of survival for non-small cell lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5373.