Mutant Lung Adenocarcinoma Research Articles

Correlation between ALK, ROS1 Biomarkers and EGFR Oncogene Mutations in Lung Tumours: Our Observations in an Apex Oncopathology Laboratory

Introduction: Analysis of Anaplastic lymphoma receptor tyrosine kinase gene (ALK), Repressor of Silencing 1 (ROS1) gene are determined by immunohistochemistry (IHC) and it is an easily applicable, cost-effective assay for potential treatment with crizotinib. Mutations of Epidermal growth factor receptor (EGFR) genes are evaluated by IHC/Multiplex RT-PCR. The purpose of this study is to assess the frequencies of ALK, ROS1 and their association with EGFR fusion gene mutations in a spectrum of lung tumours. Materials and methods: A total of 202 cases of lung tumours reported at our Center for Oncopathology from September 1st 2020 to 31st August 2021, were retrospectively analyzed for ALK, ROS1 and EGFR fusion genes based on Immunohistochemistry (IHC) and Multiplex PCR findings. ALK was tested using D5F3 clone, and ROS1 was analyzed using Cell Signalling’s D4D6 clone on the Ventana immunohistochemistry platform. EGFR status was analyzed using EGFR mutation test V2 real-time multiplex PCR assay on Roche Cobas Z480. Results: 202 biopsy samples and cellblocks of fluid aspirates were analyzed. 175/202 were histologically and immunologically proved as Non-small cell lung carcinoma (Primary pulmonary adenocarcinoma) and its metastases. 09/199 (5.23%) were Positive for ALK IHC and 03/199 (1.74%) cases had equivocal results. 06/179 (3.85%) cases were Positive for ROS1 IHC and 03/179 (1.92%) cases had equivocal results. Other histo-morphological diagnoses i.e., adenosquamous, squamous, small cell, mucinous carcinoma etc (27 cases) were all ALK and ROS1 Negative. 188/202 tumours were analyzed for EGFR mutation status, which showed 70/188 (37.23%) had specific EGFR mutations. 118/188 (62.76%) cases were EGFR wildtype. Conclusion: We observed that age related incidence of EGFR mutations was highest in elderly females, of 61 to 70 years. ALK gene mutations occurred in 6.03% and ROS1 gene mutations occurred in 5.02% of lung tumours and their metastases. EGFR-mutations were associated with ROS1 mutated lung adenocarcinomas. There are no coexistent ALK-EGFR or ALK-ROS1 mutations. All ALK IHC positive pulmonary adenocarcinomas are ROS1 negative and are mutually exclusive.

Prognostic value of KRAS G12C mutation in lung adenocarcinoma stratified by stages and radiological features

ObjectivesThe role of KRAS G12C is of particular interest given the promising clinical activity of KRAS G12C-specific inhibitors. This study comprehensively investigated the clinicopathological characteristics and prognostic value of KRAS G12C mutation in patients with surgically resected lung adenocarcinoma. MethodsData were collected on 3828 patients with completely resected primary lung adenocarcinomas who underwent KRAS mutation analysis between 2008 and 2020. The association between KRAS G12C and clinicopathologic characteristics, molecular profiles, recurrence patterns, and postoperative outcome were explored. ResultsTwo hundred seventy-five patients (7.2%) were confirmed to harbor a KRAS mutation, of whom 83 (30.2%) had the G12C subtype. KRAS G12C was more frequent in men, former/current smokers, radiologic solid nodules, invasive mucinous adenocarcinoma, and solid predominant tumors. KRAS G12C tumors had more lymphovascular invasion and higher programmed death-ligand 1 expression than KRAS wild-type tumors. TP53 (36.8%), STK11 (26.3%), and RET (18.4%) mutations were the 3 most frequent in the KRAS G12C group. Logistic regression analysis showed patients with KRAS G12C mutation were prone to experience early recurrence and locoregional recurrence. KRAS G12C mutation was found to be significantly associated with poor survival after propensity score matching. Stratified analysis showed that the KRAS G12C was an independent prognostic factor in stage I tumors and part-solid lesions, respectively. ConclusionsThe KRAS G12C mutation had a significant prognostic value in stage I lung adenocarcinomas as well as in part-solid tumors. Furthermore, it exhibited a potentially aggressive phenotype associated with early and locoregional recurrence. These findings might be relevant as better KRAS treatments are developed for clinical application.

Higher Prevalence and Poorer Prognosis of EGFR Mutant Lung Adenocarcinoma in US Hispanics

Introduction: Activating mutations in Epidermal growth factor receptor (EGFR) occur in approximately 15% White, 40-50% of Asian and 15% of Black patients with lung adenocarcinoma. However, its prevalence in the nearly 60 million U.S. Hispanics/Latinos has not been well characterized. Herein we evaluate EGFR mutation frequency in U.S. Hispanic/Latino patients with lung adenocarcinoma at an academic institute serving a large multi-ethnic area. Methods: We queried our prospective database (2015-2019) for lung adenocarcinoma patients who underwent surgical resection and had routine mutational analysis by a targeted gene panel. We identified 768 patients and were able to stratify 668 patients by self-identified race/ethnicity. We compared demographics (chi-square) and survival (Kaplan-Meier). Results: From 2015-2019, 668 patients met inclusion criteria and were evaluated for incidence of common targetable EGFR mutations. EGFR mutations were present in 30% of all patients with Hispanics/Latino experiencing an incidence of 35%, significantly more than non-Hispanic White patients, p=0.019. Overall survival at 3 years was not significantly different amongst racial/ethnic groups. However, in patients with EGFR mutations, 3-year overall survival was significantly worse in Hispanic/Latino patients in comparison to non-Hispanic White patients (62% vs 96%, p=0.021). There was no difference in the pathologic stage or surgical procedure amongst racial/ethnic groups. Discussion: Approximately one-third of U.S. Hispanics with lung adenocarcinoma displayed EGFR mutations which were associated with decreased overall survival compared to White and Asian patients. Increasing mutational analysis and investigation of biological differences of this growing ethnic group is essential for optimal targeted treatment strategies as well as in the design of future clinical trials.

Major hurdles to the use of tyrosine kinase inhibitors in clinical prevention/interception studies: Do preclinical studies with EGFR inhibitors suggest approaches to overcome some of the limitations.

There are major hurdles to the use of tyrosine kinase inhibitors (TKIs) and any other agents with significant toxicities (which means practically the preponderance of potential effective agents) in the context of prevention/anti-progression (interception) studies. We will discuss epidermal growth factor receptor (EGFR) inhibitors as examples, both in a primary prevention setting, where agent(s) are administered to individuals with no cancer but who might be considered at higher risk due to a variety of factors, and in anti-progression/interception studies, where agent(s) are administered to persons with known preinvasive lesions (e.g., colon adenomas, lung nodules, ductal carcinoma in situ (DCIS), or pancreatic intraepithelial neoplasia (PanIN) lesions in the pancreas) in an attempt to reverse or inhibit progression of these lesions. Multiple potential hurdles will be examined, including: a) toxicity of agents, b) the likely range of subtypes of cancers affected by a given treatment (e.g., EGFR inhibitors against EGFR mutant lung adenocarcinomas), c) the availability of practical endpoints besides the blocking of cancer formation or pharmacokinetics related to the agents administered in a primary prevention study, and d) the interpretation of the regression or blockage of new preinvasive lesions in the anti-progression study. Such an anti-progression approach may help address some of the factors commented on regarding primary prevention (toxicity, potential target organ cancer subtypes) but still leaves major questions regarding interpretation of modulation of preinvasive endpoints when it may not be clear how frequently they progress to clinical cancer. Additionally, we address whether certain recent preclinical findings might be able to reduce the toxicities associated with these agents and perhaps even increase their potential efficacy. Antibodies and TKIs other than the EGFR inhibitors are not discussed because few if any had been tested as monotherapies in humans, making their efficacy harder to predict, and because a number have relatively rare but quite striking toxicities. Furthermore, most of the practical hurdles raised regarding the EGFR inhibitors are relevant to the other TKIs. Finally, we briefly discuss whether early detection employing blood or serum samples may allow identification of high-risk groups more amenable to agents with greater toxicity.

Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis

BackgroundThe TP53 tumor suppressor gene is one of the most mutated genes in lung adenocarcinoma (LUAD) and plays a vital role in regulating the occurrence and progression of cancer. We aimed to elucidate the association between TP53 mutations, response to immunotherapies and the prognosis of LUAD.MethodsGenomic, transcriptomic, and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) dataset. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA). Gene set variation analysis (GSVA) were performed to determine the differences in biological pathways. A merged protein–protein interaction (PPI) network was constructed and analyzed. MSIpred was used to analyze the correlation between the expression of the TP53 gene, tumor mutation burden (TMB) and tumor microsatellite instability (MSI). CIBERSORT was used to calculate the abundance of immune cells. Univariate and multivariate Cox regression analyses were used to determine the prognostic value of TP53 mutations in LUAD.ResultsTP53 was the most frequently mutated in LUAD, with a mutational frequency of 48%. GO and KEGG enrichment analysis, GSEA, and GSVA results showed a significant upregulation of several signaling pathways, including PI3K-AKT mTOR (P < 0.05), Notch (P < 0.05), E2F target (NES = 1.8, P < 0.05), and G2M checkpoint (NES = 1.7, P < 0.05). Moreover, we found a significant correlation between T cells, plasma cells, and TP53 mutations (R2 < 0.01, P = 0.040). Univariate and multivariate Cox regression analyses revealed that the survival prognosis of LUAD patients was related to TP53 mutations (Hazard Ratio (HR) = 0.72 [95% CI, 0.53 to 0.98], P < 0.05), cancer status (P < 0.05), and treatment outcomes (P < 0.05). Lastly, the Cox regression models showed that TP53 exhibited good power in predicting three- and five-year survival rates.ConclusionsTP53 may be an independent predictor of response to immunotherapy in LUAD, and patients with TP53 mutations have higher immunogenicity and immune cell infiltration.

Novel CDK12/13 Inhibitors AU-15506 and AU-16770 Are Potent Anti-Cancer Agents in EGFR Mutant Lung Adenocarcinoma with and without Osimertinib Resistance.

Osimertinib is a third-generation epidermal growth factor receptor and tyrosine kinase inhibitor (EGFR-TKI) approved for the treatment of lung adenocarcinoma patients harboring EGFR mutations. However, acquired resistance to this targeted therapy is inevitable, leading to disease relapse within a few years. Therefore, understanding the molecular mechanisms of osimertinib resistance and identifying novel targets to overcome such resistance are unmet needs of cancer patients. Here, we investigated the efficacy of two novel CDK12/13 inhibitors, AU-15506 and AU-16770, in osimertinib-resistant EGFR mutant lung adenocarcinoma cells in culture and xenograft models in vivo. We demonstrate that these drugs, either alone or in combination with osimertinib, are potent inhibitors of osimertinib-resistant as well as -sensitive lung adenocarcinoma cells in culture. Interestingly, only the CDK12/13 inhibitor in combination with osimertinib, although not as monotherapy, suppresses the growth of resistant tumors in xenograft models in vivo. Taken together, the results of this study suggest that inhibition of CDK12/13 in combination with osimertinib has the potential to overcome osimertinib resistance in EGFR mutant lung adenocarcinoma patients.

Abstract 5935: Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data

Abstract Introduction: EGFR mutations holds the major targets for drug in lung adenocarcinoma (LUAD). Despite the tremendous study of EGFR mutant (MT) LUAD, the comprehensive interpretation of the heterogeneous character of LUAD harboring EGFR MT remains a key challenge. Here, we investigated the heterogeneity of EGFR MT LUAD and explored the tumor microenvironment (TME) in EGFR MT LUAD. Method: We performed single-cell RNA sequencing (scRNA-seq) from 135 LUAD patients which consist of normal(n=24), EGFR wild (WT)(n=18), and MT(n=93). Also, we used whole genome sequencing and bulk-RNA sequencing to validate with scRNA-seq results. From 898,648 cells, main cell types were classified. To explore the various characteristics of MT LUAD tumor cells, we used two ways: i) We re-clustered epithelial cells populating the normal, WT, and MT. ii) We re-clustered only MT epithelial cells. In each analysis, we identified the tumor character in the clusters using differential expressed genes analysis, lineage tracing, clinical information, mutation, and trajectory analysis. Also, we extracted each main cell type except epithelial cells, and identified subtypes of main cell types. Finally, we revealed the interaction of cellular components in TME. Results: In the analysis of epithelial cells, we identified characteristics of specific EGFR MT by comparing of EGFR WT and MT tumors in clusters with similar biological features. The cluster represented by alveolar type 2 (AT2) known as initiation of LUAD was populating normal, WT, and MT. In this cluster, MT- and WT-associated pathway shared but differently significant between MT and WT in the pathway analysis. The cluster represented by proliferative is mostly comprised tumor cells and we found significantly increased the expression of MDK, CD24 in the MT of the cluster. In the analysis of only MT epithelial cells, 2 of clusters were stage-specific cluster: i) The cluster annotated as early stage cluster, ii) The cluster annotated as advanced stage cluster. Trajectory showed that there is a pseudotemporal continuum, following the stage from early stage cluster to advanced stage cluster. Also, based on the lineage tracing, 2 of clusters revealed lineage-specific clusters: i) The cluster annotated as AT2 was enriched from early stage cells, ii) The cluster annotated as basal cell known as origin of lung squamous cell carcinoma(LUSC) was enriched from advanced stage cells. Psedotemporal ordering of these cluster revealed AT2 cluster transdifferentiate into basal cell cluster which implied the possibility of LUAD to LUSC transition by drug resistance. In the interaction of MT and WT TME, the number of signaling received epithelial cells from myeloid cells, endothelial cells, and fibroblasts as sender increased compared with the interaction of normal. Conclusion: We shed light on the ecosystem of TME according to clinical and biological feature of tumor in EGFR mutant LUAD. Citation Format: You Won Lee, Eun Ji Lee, Seung Yeon Oh, Kyoung-Ho Pyo, Seong Gu Heo, YoungJoon Park, Su-Jin Choi, Kyumin Lim, Ju-hyeon Lee, Jae Hwan Kim, Jii Bum Lee, Ji Yoon Lee, Sun Min Lim, Chang Gon Kim, Min Hee Hong, Mi Ran Yun, Byoung Chul Cho. Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data. [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 5935.

Abstract 857: Assuming tumors have a spherical shape in modeling EGFR mutant lung adenocarcinoma: Impact on modeled clinical outcome

Abstract Introduction The in silico epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma (ISELA) model predicts tumor progression in patients with advanced EGFR-mutated lung adenocarcinoma [1]. To investigate model credibility, we dug into a simplifying assumption made in the ISELA model and in other models [2][3], namely the assumption that tumors have a spherical shape. The validity of the spherical assumption (SA) is assessed by analyzing two lung cancer datasets, and its impact on the model is assessed by comparing predictions of the ISELA model with different shape hypotheses. Material and Methods To evaluate the impact of tumor shape assumptions on the estimated tumor volume with respect to real-world data, two lung cancer datasets [4][5] were analyzed to appraise the sphericity of lung tumors. As individual longest tumor radii were available for each tumor, the estimated spherical volume was computed under the SA and compared to the reported tumor volume. The ellipsoid assumption (EA) was also explored as an alternative -less simplifying- shape assumption. As the three tumor axes are rarely reported and were unavailable in these datasets, the three tumor axes in the EA were defined with proportionality relationships to the longest available radius. The estimated elliptical volume was then compared to the measured volume. To quantify the impact of the SA on the model’s primary output, time to progression (TTP), an alternative ISELA model assuming ellipsoid tumors was implemented. Two clinical trial simulations -one under the SA and the other under the EA- were performed on the same virtual patients with only the sphericity parameter differing, thus allowing a patient per patient comparison. Results The datasets analysis revealed that under the SA the tumor volume was overestimated in most cases, whereas under the EA the tumor volume was better approximated. On average, tumors had their shortest axis equal to 0.7 times their longest radius. Comparison of predictions between simulations showed that only 5% of the virtual patients changed their treatment response status (non-responder/responder). In patients classified as responding to the treatment in both simulations, the median TTP difference was 14 days. Conclusion Both real data and in silico simulations enabled us to better understand to which extent the SA is a simplifying but yet credible assumption in modeling lung cancer progression. Considering ellipsoid tumors is nevertheless a promising alternative as it better predicts tumor volume. Additional studies are needed to further explore its use as support to clinical decision making.

Abstract 4454: Loss of CX3CL1 expression mediates immune evasion in STK11 mutated lung adenocarcinomas

Abstract Immunotherapy has improved survival for many cancer patients, especially for immunogenic malignancies such as lung cancer. However, even in lung cancer, the response rate for anti-PD1 therapy (for example) does not exceed 20%. Thus, it is critical to identify mechanisms that block the response to immune checkpoint therapies. STK11 (also known as LKB1) is encoded by the serine threonine kinase 11 gene (STK11). Patients harboring tumors with STK11 mutations have reduced infiltrates of cytotoxic T-cells and clinical studies have shown that they respond poorly to anti-PD1 or anti-PDL-1 therapies regardless of PDL-1 status, which otherwise predicts benefit. Herein, we have used gene expression data from a cohort of 442 lung adenocarcinoma patients to identify CX3CL1 (fractalkine) as a gene silenced in STK11 mutant tumors with potential to be a key direct modulator of the immune system relevant to STK11 loss. To further explore this hypothesis, we have edited the STK11 gene in A549 cells back to wild type (STK11 corrected). As predicted, restoration of STK11 function resulted in modest expression of CX3CL1 as measured by Western blotting. Unexpectedly, exposure of STK11 corrected cells to human immune cells isolated from the blood of healthy donors resulted in a 5 to 10-fold increase in CX3CL1 suggesting interactive signaling between tumor and immune cells. Using transwell assays and STK11 corrected A549 cells we find that restoration of functional STK11 increases immune cell migration, adhesion and invasion in vitro. Finally, cytotoxicity assays demonstrate that STK11 corrected A549 cells are 3 to 5-fold more sensitive to immune cell killing. Taken together these results suggest the hypothesis that CX3CL1 loss mediates immune evasion in STK11 mutant lung adenocarcinomas. Future work will further explore the mechanisms underlying this pathway in preclinical models. Citation Format: Eria Eksioglu, Gabriela M. Wright, Trent R. Percy, Kenneth L. Wright, W. Douglas Cress. Loss of CX3CL1 expression mediates immune evasion in STK11 mutated lung adenocarcinomas. [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 4454.

Abstract 4904: Glutamine antagonist DRP-104 enhances anti-tumor responses in KEAP1 mutant lung cancer

Abstract KEAP1 is mutated in approximately 20% of non-small cell lung cancer (NSCLC) and is associated with poor response rates to checkpoint blockade. Given the therapeutic challenge presented by KEAP1 mutant tumors and the great potential held by immunotherapeutic approaches, there is an urgent need to identify the mechanisms that mediate immune evasion in patients with KEAP1 mutant lung adenocarcinoma. We previously demonstrated that metabolic rewiring in KEAP1 mutant tumors leads to increased dependency on glutamine as a substrate for multiple anabolic pathways. DRP-104 (Sirpiglenastat) is a novel glutamine antagonist which inhibits all glutamine consuming reactions. Using pre-clinical mouse models and patient derived xenograft models we demonstrate that DRP-104 robustly impairs the growth of KEAP1 mutant tumors. Furthermore, using an immunocompetent orthotopic lung adenocarcinoma mouse model we find that treatment with DRP-104 increases survival of Keap1 mutant tumor bearing mice treated with anti-PD1 therapy. We have dissected the mechanism by which DRP-104 impacts KEAP1 mutant tumors and the surrounding immune microenvironment. Notably, DRP-104 impairs nucleotide synthesis in KEAP1 mutant tumors and thereby inhibits cancer cell growth. In addition, DRP-104 reduces exhausted T cell and T regulatory populations within the tumor microenvironment as well as increases effector T cell function. Overall, we find that DRP-104 impairs the growth of KEAP1 mutant tumors through both targeting of tumor intrinsic metabolic vulnerabilities and through tumor extrinsic immunostimulatory mechanisms such as promoting the expansion of functional anti-tumor T cell populations. This data provides additional rationale for the ongoing phase I/II clinical trial (NCT04471415) using DRP-104 in NSCLC with mutations in KEAP1 as well as for combining DRP-104 with checkpoint blockade. Citation Format: Ray Pillai, Sarah LeBoeuf, Ali Rashidfarrokhi, Shih Ming Huang, Triantafyllia Karakousi, Anastasia-Maria Zavitsanou, Warren Wu, Volkan Sayin, Robert Wild, Sergei Koralov, Thales Papagiannakopoulos. Glutamine antagonist DRP-104 enhances anti-tumor responses in KEAP1 mutant 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 4904.

Abstract 856: Comparison of the effect of two EGFR-TKI in patients with EGFR-mutant lung adenocarcinoma using in silico clinical trials

Abstract Introduction: 16,4% of lung adenocarcinomas (LUAD) are presenting a mutation in the Epidermal Growth Factor Receptor (EGFR), as reported in the Epidemiological Strategy and Medical Economics database[1], resulting in its constitutive activation and leading to uncontrolled cell proliferation. While some tyrosine kinase inhibitors (TKIs) have been developed to target EGFR mutations, their efficacy is not long-lasting, due to the emergence of resistance mutations[2]. Based on in silico approaches, we investigate and compare the impact of two TKIs (1st and 3rd generation) on tumor size evolution and clinical outcome, depending on the target population. Materials and Methods: We developed in Novadiscovery's jinkō platform a detailed mechanistic disease model of EGFR-mutant LUAD that predicts patients’ disease progression, based on their characteristics. We added on top of this disease model, a mechanistic physiologically-based pharmaco-kinetics model for each TKI drug, integrating their mechanisms of action. Publicly available data were used to calibrate the drug models and assess their credibility.We used the combination of the disease model with the two drug models to simulate clinical trials to compare the impact of both drugs on the course of the disease. Results:Both the 1st and 3rd generation TKI drug models can reproduce the pharmacokinetics in mice and humans. Combination of these models with the EGFR-mutant LUAD disease model is used to predict the tumor evolution in mice and the clinical outcome in humans. Differences in disease progression between treatments are observed according to the patients’ tumor mutational profiles. Discussion and Conclusion: The knowledge based construction of this EGFR mutant LUAD disease and treatment model successfully reproduced publicly available real-world data and will be challenged to reproduce the results from the FLAURA trial for an additional step of validation. The credibility of the model thereby acquired is a first step in the use of the model to compare existing treatments to investigational treatments and further support innovative therapies development. As such, in silico approaches are a complementary and valuable tool to existing in vitro or in animal experiments, alongside with clinical trials performance.

Abstract 652: Tumor cell-specific IL-1/IL-1R signaling promotes KRAS mutant lung tumorigenesis

Abstract Despite improved diagnosis and treatment strategies such as immunotherapy, lung cancer is still the leading cause of cancer-related deaths worldwide in both men and women. Lung adenocarcinoma (LUAD) with driver mutations in the KRAS oncogene is the most prevalent molecular subtype of lung cancer. KRAS mutant LUAD exhibits aggressive biology in part due to enhanced pro-tumor inflammation mediated by activation of the nuclear factor-κB (NF-κB) and, consequently, elevated expression of various cytokines. While the pro-inflammatory cytokine IL-1β is a product of the NF-κB pathway it also acts as a potent activator, further amplifying the production of protumor cytokines via a positive feedback loop. We have shown that IL-1β blockade enhances anti-tumor immune responses while inhibiting immunosuppression in a mouse model of KRAS mutant LUAD driven by lung epithelial cell-specific expression of KRASG12D (CCSPCre/LSL-KRASG12D, CC-LR mouse). Cell lineage-specific mechanisms that underlie these anti-tumor effects following inhibition of IL-1β are still poorly understood. To fill this void, we here explored the effects of targeting the IL-1R receptor in KRAS mutant lung epithelial cells in the CC-LR mouse model. We studied tumor development and host immune response in 14-week-old CC-LR mice with conditional knockout of IL-1R in KRAS mutant lung epithelial cells (LR/IL-1RΔ/Δ) in comparison to age- and sex-matched control CC-LR littermates. LR/IL-1RΔ/Δ mice displayed markedly reduced tumor multiplicity (~50%) when compared to control CC-LR mice concomitant with decreased cell proliferation and angiogenesis evidenced by attenuated immunohistochemical expression of Ki-67 and ERG. Flow cytometry analysis showed an elevated inflammatory response, most evidently seen through the significant increase in infiltrating monocytes. Interestingly, a shift in type-1 conventional dendritic cells, commonly involved in antigen-cross presentation in tumorigenesis, to type-2 conventional dendritic cells was seen in LR/IL-1RΔ/Δ mice, suggesting a different method of cross-presentation resulting from the conditional knockout of IL-1R that could potentially lead to a protective T-cell response. These results were further confirmed via gene expression analysis of respective markers. Our findings provide further support for the role of the IL-1 cytokine family in the development and progression of KRAS mutant LUAD as well as warrant further studies targeted towards understanding the mechanistic effects IL-1β has on the tumor microenvironment. Citation Format: Avantika Krishna, Michael J. Clowers, Bo Yuan, Milind Mutala, Maria Jose Arredondo Sancristobal, Jocelynn Colunga, Ryan De Maleki, Linda Phan, Humam Kadara, Seyed Javad Moghaddam. Tumor cell-specific IL-1/IL-1R signaling promotes KRAS mutant lung tumorigenesis [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 652.

Investigation of the combination of intratumoral and peritumoral radiomic signatures for predicting epidermal growth factor receptor mutation in lung adenocarcinoma.

We investigated optimal peritumoral size and constructed predictive models for epidermal growth factor receptor (EGFR) mutation. A total of 164 patients with lung adenocarcinoma were retrospectively analyzed. Radiomic signatures for the intratumoral region and combinations of intratumoral and peritumoral regions (3, 5, and 7mm) from computed tomography images were extracted using analysis of variance and least absolute shrinkage. The optimal peritumoral region was determined by radiomics score (rad-score). Intratumoral radiomic signatures with clinical features (IRS) were used to construct predictive models for EGFR mutation. Combinations of intratumoral and 3, 5, or 7mm-peritumoral signatures with clinical features (IPRS3, IPRS5, and IPRS7, respectively) were also used to construct predictive models. Support vector machine (SVM), logistic regression (LR), and LightGBM models with five-fold cross-validation were constructed, and the receiver operating characteristics were evaluated. Area under the curve (AUC) of the training and test cohorts values were calculated. Brier scores (BS) and decision curve analysis (DCA) were used to evaluate the predictive models. The AUC values of the SVM, LR, and LightGBM models derived from IRS were 0.783 (95% confidence interval: 0.602-0.956), 0.789 (0.654-0.927), and 0.735 (0.613-0.958) for training, and 0.791 (0.641-0.920), 0.781 (0.538-0.930), and 0.734 (0.538-0.930) for test cohort, respectively. Rad-score confirmed that the 3mm-peritumoral size was optimal (IPRS3), and AUCs values of SVM, LR, and lightGBM models derived from IPRS3 were 0.831 (0.666-0.984), 0.804 (0.622-0.908), and 0.769 (0.628-0.921) for training and 0.765 (0.644-0.921), 0.783 (0.583-0.921), and 0.796 (0.583-0.949) for test cohort, respectively. The BS and DCA of the LR and LightGBM models derived from IPRS3 were better than those from IRS. Accordingly, the combination of intratumoral and 3mm-peritumoral radiomic signatures may be helpful for predicting EGFR mutations.

80 - Characteristics and outcomes in patients with KRAS mutated lung adenocarcinomas: a retrospective data analysis

80 - Characteristics and outcomes in patients with KRAS mutated lung adenocarcinomas: a retrospective data analysis

Heterogeneous pattern of gene expression driven by TTN mutation is involved in the construction of a prognosis model of lung squamous cell carcinoma.

To investigate the impact that TTN mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma. In this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the TTN mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset. The incidence of TTN mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for TTN mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis. Our data showed that the gene heterogeneity expression, which was driven by TTN mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of TTN gene mutations in lung adenocarcinoma.

Glucocorticoid mediated inhibition of LKB1 mutant non-small cell lung cancers.

The glucocorticoid receptor (GR) is an important anti-cancer target in lymphoid cancers but has been understudied in solid tumors like lung cancer, although glucocorticoids are often given with chemotherapy regimens to mitigate side effects. Here, we identify a dexamethasone-GR mediated anti-cancer response in a subset of aggressive non-small cell lung cancers (NSCLCs) that harbor Serine/Threonine Kinase 11 (STK11/LKB1) mutations. High tumor expression of carbamoyl phosphate synthase 1 (CPS1) was strongly linked to the presence of LKB1 mutations, was the best predictor of NSCLC dexamethasone (DEX) sensitivity (p < 10-16) but was not mechanistically involved in DEX sensitivity. Subcutaneous, orthotopic and metastatic NSCLC xenografts, biomarker-selected, STK11/LKB1 mutant patient derived xenografts, and genetically engineered mouse models with KRAS/LKB1 mutant lung adenocarcinomas all showed marked in vivo anti-tumor responses with the glucocorticoid dexamethasone as a single agent or in combination with cisplatin. Mechanistically, GR activation triggers G1/S cell cycle arrest in LKB1 mutant NSCLCs by inducing the expression of the cyclin-dependent kinase inhibitor, CDKN1C/p57(Kip2). All findings were confirmed with functional genomic experiments including CRISPR knockouts and exogenous expression. Importantly, DEX-GR mediated cell cycle arrest did not interfere with NSCLC radiotherapy, or platinum response in vitro or with platinum response in vivo. While DEX induced LKB1 mutant NSCLCs in vitro exhibit markers of cellular senescence and demonstrate impaired migration, in vivo DEX treatment of a patient derived xenograft (PDX) STK11/LKB1 mutant model resulted in expression of apoptosis markers. These findings identify a previously unknown GR mediated therapeutic vulnerability in STK11/LKB1 mutant NSCLCs caused by induction of p57(Kip2) expression with both STK11 mutation and high expression of CPS1 as precision medicine biomarkers of this vulnerability.

Predicting EGFR mutational status from pathology images using a real-world dataset

Treatment of non-small cell lung cancer is increasingly biomarker driven with multiple genomic alterations, including those in the epidermal growth factor receptor (EGFR) gene, that benefit from targeted therapies. We developed a set of algorithms to assess EGFR status and morphology using a real-world advanced lung adenocarcinoma cohort of 2099 patients with hematoxylin and eosin (H&E) images exhibiting high morphological diversity and low tumor content relative to public datasets. The best performing EGFR algorithm was attention-based and achieved an area under the curve (AUC) of 0.870, a negative predictive value (NPV) of 0.954 and a positive predictive value (PPV) of 0.410 in a validation cohort reflecting the 15% prevalence of EGFR mutations in lung adenocarcinoma. The attention model outperformed a heuristic-based model focused exclusively on tumor regions, and we show that although the attention model also extracts signal primarily from tumor morphology, it extracts additional signal from non-tumor tissue regions. Further analysis of high-attention regions by pathologists showed associations of predicted EGFR negativity with solid growth patterns and higher peritumoral immune presence. This algorithm highlights the potential of deep learning tools to provide instantaneous rule-out screening for biomarker alterations and may help prioritize the use of scarce tissue for biomarker testing.

Genotype-phenotype mapping of a patient-derived lung cancer organoid biobank identifies NKX2-1-defined Wnt dependency in lung adenocarcinoma

Human lung cancer is a constellation of tumors with various histological and molecular properties. To build a preclinical platform that covers this broad disease spectrum, we obtained lung cancer specimens from multiple sources, including sputum and circulating tumor cells, and generated a living biobank consisting of 43 lines of patient-derived lung cancer organoids. The organoids recapitulated the histological and molecular hallmarks of the original tumors. Phenotypic screening of niche factor dependency revealed that EGFR mutations in lung adenocarcinoma are associated with the independence from Wnt ligands. Gene engineering of alveolar organoids reveals that constitutive activation of EGFR-RAS signaling provides Wnt independence. Loss of the alveolar identity gene NKX2-1 confers Wnt dependency, regardless of EGFR signal mutation. Sensitivity to Wnt-targeting therapy can be stratified by the expression status of NKX2-1. Our results highlight the potential of phenotype-driven organoid screening and engineering for the fabrication of therapeutic strategies to combat cancer.

Applications of radiomics-based analysis pipeline for predicting epidermal growth factor receptor mutation status

BackgroundThis study aimed to develop a pipeline for selecting the best feature engineering-based radiomic path to predict epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma in 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT).MethodsThe study enrolled 115 lung adenocarcinoma patients with EGFR mutation status from June 2016 and September 2017. We extracted radiomics features by delineating regions-of-interest around the entire tumor in 18F-FDG PET/CT images. The feature engineering-based radiomic paths were built by combining various methods of data scaling, feature selection, and many methods for predictive model-building. Next, a pipeline was developed to select the best path.ResultsIn the paths from CT images, the highest accuracy was 0.907 (95% confidence interval [CI]: 0.849, 0.966), the highest area under curve (AUC) was 0.917 (95% CI: 0.853, 0.981), and the highest F1 score was 0.908 (95% CI: 0.842, 0.974). In the paths based on PET images, the highest accuracy was 0.913 (95% CI: 0.863, 0.963), the highest AUC was 0.960 (95% CI: 0.926, 0.995), and the highest F1 score was 0.878 (95% CI: 0.815, 0.941). Additionally, a novel evaluation metric was developed to evaluate the comprehensive level of the models. Some feature engineering-based radiomic paths obtained promising results.ConclusionsThe pipeline is capable of selecting the best feature engineering-based radiomic path. Combining various feature engineering-based radiomic paths could compare their performances and identify paths built with the most appropriate methods to predict EGFR-mutant lung adenocarcinoma in 18FDG PET/CT. The pipeline proposed in this work can select the best feature engineering-based radiomic path.

Risk Factors for Recurrence of Stage I Epidermal Growth Factor Receptor Mutated Lung Adenocarcinoma

BackgroundWe aimed to clarify the risk factors for postoperative recurrence in patients with epidermal growth factor receptor (EGFR)-mutated stage I lung adenocarcinoma, using EGFR wild-type adenocarcinoma as a comparator, to select optimal candidates for adjuvant therapy with EGFR tyrosine kinase inhibitor (TKI). MethodsData of patients with pathologic stage I EGFR-mutated (n = 713) and wild-type (n = 673) adenocarcinoma who did not receive adjuvant therapy were retrospectively analyzed. The cumulative incidence of recurrence (CIR) was estimated using Gray’s method, and multivariable Fine-Gray competing risk models identified independent risk factors associated with recurrence. ResultsThe CIR did not differ significantly between patients with EGFR-mutated and wild-type adenocarcinoma (P = .32). Multivariable analysis revealed that greater size (cm) of invasive tumor (hazard ratio 1.539; 95% CI, 1.077-2.201), lymphovascular invasion (hazard ratio 5.180; 95% CI, 2.208-12.15), pleural invasion (hazard ratio 3.388; 95% CI, 1.524-7.533), and high-grade histologic subtype (hazard ratio 4.295; 95% CI, 1.539-11.99) were independent risk factors for recurrence in patients with EGFR-mutated adenocarcinoma. The 5-year CIR was significantly higher among patients with these factors (tumor size greater than 2 cm, 15.9%; lymphovascular invasion, 26.9%; pleural invasion, 39.3%; and high-grade subtype, 44.4%) than among patients without them (4.4%, 2.2%, 3.9%, and 5%, respectively; P < .001). For patients with EGFR wild-type adenocarcinoma, independent risk factors for recurrence were invasive tumor size, lymphovascular invasion, and pleural invasion, but not histologic subtypes. ConclusionsEven for patients with EGFR-mutated stage I lung adenocarcinoma, recurrence risk is stratified. Adjuvant therapy may be considered if they have high-risk factors for recurrence.