KEAP1-driven co-mutations in lung adenocarcinoma unresponsive to immunotherapy despite high tumor mutational burden

Resistance in Lung Cancer Immunotherapy and How to Overcome It: Insights from the Genetics Perspective and Combination Therapies Approach

Lung cancer with the highest number of new cases diagnosed in Europe and in Poland, remains an example of malignancy with a very poor prognosis despite the recent progress in medicine. Different treatment strategies are now available for cancer therapy based on its type, molecular subtype and other factors including overall health, the stage of disease and cancer molecular profile. Immunotherapy is emerging as a potential addition to surgery, chemotherapy, radiotherapy or other targeted therapies, but also considered a mainstay therapy mode. This combination is an area of active investigation in order to enhance efficacy and overcome resistance. Due to the complexity and dynamic of cancer's ecosystem, novel therapeutic targets and strategies need continued research into the cellular and molecular mechanisms within the tumour microenvironment. From the genetic point of view, several signatures ranging from a few mutated genes to hundreds of them have been identified and associated with therapy resistance and metastatic potential. ML techniques and AI can enhance the predictive potential of genetic signatures and model the prognosis. Here, we present the overview of already existing treatment approaches, the current findings of key aspects of immunotherapy, such as immune checkpoint inhibitors (ICIs), existing molecular biomarkers like PD-L1 expression, tumour mutation burden, immunoscore, and neoantigens, as well as their roles as predictive markers for treatment response and resistance.

Construction of ubiquitination-related risk model for predicting prognosis in lung adenocarcinoma

Lung adenocarcinoma is the most prevalent lung cancer type. Ubiquitination, a critical post-translational modification process that regulates protein degradation and signaling pathways, has been implicated in various cancers, including LUAD. We aimed to explore the associations between ubiquitination and lung adenocarcinoma. TCGA-LUAD cohort served as the training set. Unsupervised clustering, univariate Cox regression, Random Survival Forests, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied to identify ubiquitination-related genes (URGs), then ubiquitination-related risk scores (URRS) were calculated using gene expression and the univariate Cox's coefficient. Comparisons between the high and the low URRS group regarding chemotherapy drug response, immune infiltration level, tumor mutation burden (TMB), tumor neoantigen load (TNB), PD1/L1 expression, and enriched pathways were performed. URRS was calculated based on the expression of DTL, UBE2S, CISH, and STC1. Patients with higher URRS had a worse prognosis (Hazard Ratio [HR] = 0.54, 95% Confidence Interval [CI]: 0.39-0.73, p < 0.001), and the prognosis of the URRS was further confirmed in 6 external validation cohorts (Hazard Ratio [HR] = 0.58, 95% Confidence Interval [CI]: 0.36-0.93, pmax = 0.023). The high URRS group had higher PD1/L1 expression level (p < 0.05), TMB (p < 0.001), TNB (p < 0.001), and TME scores (p < 0.001). The IC50 values of various chemotherapy drugs were lower in the high URRS group. In addition, we found that upregulation of STC1, UBE2S, and DTL was associated with worse, while upregulation of CISH was associated with better prognosis. We also performed a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for validation. In conclusion, the ubiquitination-based signature might serve as a biomarker to help evaluate the prognosis, biological features, and appropriate treatment for patients with lung adenocarcinoma.

Global research trends of tumor microenvironment in non-small cell lung cancer with epidermal growth factor receptor mutation: a bibliometric analysis from 2014 to 2023

Purpose

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and about half of the patients had mutations in the epidermal growth factor receptor (EGFR) gene. Changes in the tumor microenvironment after EGFR mutation are closely related to tumor progression and treatment efficacy.

Materials and methods

We searched the Web of Science Core Collection database to select the articles related to tumor microenvironment in non-small cell lung cancer with epidermal growth factor receptor mutation. The countries/regions, institutes, authors, journals, references, and keywords were visualized and analyzed.

Results

227 relevant studies were obtained from WoSCC. These articles came from 102 countries and 1179 institutions. After network analysis, it was found that the intensity of USA cooperation with China was the greatest (LS=13), followed by cooperation with South Korea (LS=3) and with Japan (LS=3). A total of 2267 authors participated the all 227 articles. 112 journals were covered, and Frontiers in Oncology published most papers (n=16, 14.3%). A total of 7964 co-cited references are related to TME in NSCLC with EGFR mutation. "EGFR" is the keyword with the highest centrality (C=0.31) and first appeared. The keywords that burst in the last 1 year (2022-2023) are "immunotherapy", "mechanism", "lung neoplasms", "T cells", and "multicenter".

Conclusion

Effective drug treatment of advanced NSCLC with EGFR mutations after failure of first-line chemotherapy is one of the hotspots, in which the efficacy of immune checkpoint inhibitors may be the direction of the current and future studies that need to find a breakthrough.

Classification of lung adenocarcinoma based on senescence-related genes identifies a cluster with immunotherapy resistance and poor prognosis

Lung adenocarcinoma is one of the major contributors to cancer-related mortality, with immunotherapy emerging as a key treatment. However, many patients exhibit resistance to immune checkpoint inhibitors. Cellular senescence has been linked to tumor progression and drug resistance, influencing the tumor microenvironment. This study applied consensus clustering to classify lung adenocarcinoma patients into two clusters based on senescence-related gene expression, revealing differing immune characteristics. One of the identified clusters exhibited immunosuppressive characteristics and showed resistance to immunotherapy. A senescence-related risk score was developed using machine learning to predict immunotherapy response and prognosis. High senescence-related risk score correlated with poorer survival and increased immunotherapy resistance across multiple cancer types. The senescence-related risk score model showed robust predictive ability in both the training and validation cohorts. These findings suggest a link between senescence and immunotherapy resistance, and further investigation into their relationship could reveal new perspectives for cancer treatment.

Lung adenocarcinomas with mucinous histology: clinical, genomic, and immune microenvironment characterization and outcomes to immunotherapy-based treatments and KRASG12C inhibitors

BACKGROUND

Approximately 10% of lung adenocarcinomas (LUADs) have mucinous histology (LUADMuc), which is associated with a light/absent smoking history and a high prevalence of KRAS mutations. We sought to characterize LUADMuc by comparing it with LUAD without mucinous histology (LUADnon-muc) and determine the relative benefit of current treatments.

PATIENTS AND METHODS

Patients with LUAD from five institutions and The Cancer Genome Atlas Pan-Cancer Atlas classified as LUADMuc or LUADnon-muc were included. Clinicopathologic, genomic, immunophenotypic, transcriptional features, and treatment outcomes were compared between LUADMuc and LUADnon-muc.

RESULTS

Of 4082 patients with LUAD, 9.9% had LUADMuc. Compared with LUADnon-muc, patients with LUADMuc had a lighter smoking history (median 15 versus 20 pack-years; P = 0.008), lower programmed death-ligand 1 (PD-L1) tumor proportion score (median 0% versus 5%, P < 0.0001), and lower tumor mutation burden (median 6.8 versus 8.5 mutations/megabase, P < 0.0001). Mutations in KRAS, NKX2-1 [thyroid transcription factor 1 (TTF-1)], STK11, SMARCA4, GNAS, and ALK rearrangements were enriched in LUADMuc, while TP53, EGFR, BRAF, and MET mutations were enriched in LUADnon-muc. At stage IV diagnosis, LUADMuc was more likely to have contralateral lung metastasis (55.2% versus 36.9%, P < 0.0001) and less likely to have brain metastases (23.3% versus 41.9%, P < 0.0001). Compared with LUADnon-muc, LUADMuc cases showed lower intratumor CD8+, PD-1+, CD8+PD-1+, and FOXP3+ cells. Among metastatic cases receiving immune checkpoint inhibitors, compared with LUADnon-muc (n = 1511), LUADMuc (n = 112) had a lower objective response rate (ORR 8.4% versus 25.9%, P < 0.0001), and shorter median progression-free survival (mPFS 2.6 versus 3.9 months, P < 0.0001) and overall survival (mOS 9.9 versus 17.2 months, P < 0.0001). Similarly, patients with LUADMuc had worse outcomes to chemoimmunotherapy. LUADMuc (n = 18) and LUADnon-muc (n = 150) had similar ORR (16.7% versus 34.9%, P = 0.12) and mPFS (4.6 versus 5.6 months, P = 0.17) to treatment with KRASG12C inhibitors, but LUADMuc had shorter mOS (6.8 versus 10.8 months, P = 0.018).

CONCLUSIONS

LUADMuc represents a distinct LUAD subpopulation with unique clinicopathologic, genomic, immunophenotypic, and transcriptional features, achieving worse outcomes to standard immunotherapy-based treatments.

Clinical characteristics and prognostic analysis of patients with SMARCA4-deficient lung cancer

BackgroundSMARCA4-deficient NSCLC is a rare type of tumor, accounting for approximately 10% of all NSCLC. It exhibits a weak response to conventional chemotherapy and has a poor prognosis, and lacks alterations in EGFR (epidermal growth factor receptor), ALK (anaplastic lymphoma kinase), and ROS1 (ROS proto-oncogene 1) genes Therefore, the mechanisms of SMARCA4 in NSCLC development urgently need to be explored to identify novel biomarkers and precise therapeutic strategies for this subtype.ObjectiveThe aim of this study was to understand the clinical characteristics of this special type of tumor and its response to different treatments.MethodsWe collected clinical data from 42 patients with SMARCA4-deficient NSCLC from July 2022 to January 2024, and analyzed their clinical features and survival state.ResultsThe study included a total of 42 patients diagnosed with NSCLC and harboring SMARCA4 mutation. The majority of these patients were male with a median age of 67 years. Most patients presented at stage IV upon diagnosis with highly aggressive tumors characterized by high Ki-67 proliferation index values resulting in poor overall prognosis. Genetic testing revealed TP53 gene mutations to be most prevalent (21%), followed by KRAS mutations (13%). Patients receiving immunotherapy exhibited significantly longer median overall survival compared to those treated solely with chemotherapy. Targeted drug therapy demonstrated favorable effects in some patients.ConclusionNSCLC patients harboring SMARCA4 deficiency exhibit poor overall survival rates with a median overall survival time of 5.4 months. Immunotherapy may provide benefits for NSCLC patients with SMARCA4 deficiency.

Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes

In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mutations to identify key mutations that are most significantly correlated to ICB response. We proposed a classifier, Gene mutation-based Predictive Signature (GPS), to categorize patients based on their predicted response and clinical outcomes post-ICB therapy. GPS outperformed conventional predictors when validated in independent cohorts. Multi-omics analysis and multiplex immunohistochemistry (mIHC) revealed insights into tumor immunogenicity, immune responses, and the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) across different GPS groups. Finally, we validated distinct responses of different GPS samples to ICB in an ex-vivo tumor organoid-PBMC co-culture model. Overall, our findings highlight a simple, robust classifier for accurate ICB response prediction, which could reduce costs, shorten testing times, and facilitate clinical implementation.

Utilizing Nanoparticles to Overcome Anti-PD-1/PD-L1 Immunotherapy Resistance in Non-Small Cell Lung cancer: A Potential Strategy

Lung cancer is the leading cause of cancer-related mortality globally, with non-small cell lung cancer (NSCLC) constituting 85% of cases. Immune checkpoint inhibitors (ICIs) represented by anti-programmed cell death protein 1 (PD-1)/ programmed cell death ligand 1 (PD-L1) have emerged as a promising frontier in cancer treatment, effectively extending the survival of patients with NSCLC. However, the efficacy of ICIs exhibits significant variability across diverse patient populations, with a substantial proportion showing poor responsiveness and acquired resistance in those initially responsive to ICIs treatments. With the advancement of nanotechnology, nanoparticles offer unique advantages in tumor immunotherapy, including high permeability and prolonged retention(EPR) effects, enhanced drug delivery and stability, and modulation of the inflammatory tumor microenvironment(TME). This review summarizes the mechanisms of resistance to ICIs in NSCLC, focusing on tumor antigens loss and defective antigen processing and presentation, failure T cell priming, impaired T cell migration and infiltration, immunosuppressive TME, and genetic mutations. Furthermore, we discuss how nanoparticles, through their intrinsic properties such as the EPR effect, active targeting effect, shielding effect, self-regulatory effect, and synergistic effect, can potentiate the efficacy of ICIs and reverse resistance. In conclusion, nanoparticles serve as a robust platform for ICIs-based NSCLC therapy, aiding in overcoming resistance challenges.

Clinicopathologic and genomic analyses of SMARCA4-mutated non-small cell lung carcinoma implicate the needs for tailored treatment strategies

BACKGROUND

The clinicopathologic and therapeutic significance of SMARCA4 mutation in non-small cell lung carcinoma (NSCLC) remains unclear.

METHODS

We retrieved 575 NSCLC cases from the clinical target sequencing cohort (N = 2157) to compare the clinicopathologic characteristics of groups subclassified based on the presence of truncated or non-truncated SMARCA4 mutations (SMARCA4-truncated, SMARCA4-non-truncated, and SMARCA4-wild type [WT]). The differences in gene expression profiles between these groups were evaluated using the TCGA-LUAD dataset.

RESULTS

Fifty (2.3%) SMARCA4-truncated and 63 (2.9%) SMARCA4-non-truncated NSCLCs were identified. The majority of SMARCA4-truncated NSCLCs were present in male smokers (94.0%) and pathologically diagnosed as adenocarcinoma (76.0%). The SMARCA4-truncated group showed rare targetable driver alterations with a higher tumor mutation burden than the SMARCA4-WT group. Gene expression profile analysis revealed that cancer/testis antigen (CTA) expression was enriched in the SMARCA4-truncated group, with up to 57% of the cases displaying immunoreactivities for MAGEA4, CT45A, and/or PRAME. The SMARCA4-non-truncated group showed heterogeneous clinicopathologic, genomic, and immunohistochemical features that fell between SMARCA4-truncated and WT groups. Both SMARCA4-truncated and non-truncated groups showed significantly poor prognosis with pemetrexed-platinum chemotherapy, yet there was no significant difference in survival following immune checkpoint inhibitor monotherapy.

CONCLUSION

SMARCA4-truncated NSCLC represents a variant of driver-negative NSCLC, mainly occurring in male smokers with poorly differentiated adenocarcinoma histology. In contrast, SMARCA4-non-truncated NSCLC indicates a heterogeneous subpopulation, exhibiting intermediate characteristics between the SMARCA4-truncated and SMARCA4-WT groups. While showing poor response to pemetrexed-platinum chemotherapy, increased CTA expression could be a novel therapeutic target in SMARCA4-mutated NSCLCs.

Intracranial Disease Control and Survival among Patients with KRAS-mutant Lung Adenocarcinoma and Brain Metastases Treated with Stereotactic Radiosurgery

PURPOSE

Precision medicine according to molecularly defined subgroups offers great potential to improve outcomes for patients with metastatic lung adenocarcinoma. This study describes clinical outcomes and the impact of co-occurring genetic alterations on outcomes following stereotactic radiosurgery (SRS) among patients with Kirsten rat sarcoma viral oncogene homolog (KRAS)-mutant lung adenocarcinoma.

METHODS AND MATERIALS

A total of 195 patients with KRAS-mutant lung adenocarcinoma were treated with SRS for brain metastases (BMs) between 2014 and 2018 with follow-up until 2022 or death. Coprimary outcomes were median overall survival (OS) and intracranial progression-free survival (iPFS); univariable and multivariable Cox regression models and Kaplan-Meier survival analysis were used.

RESULTS

Median follow-up from the date of BM diagnosis was 11 months. Median OS and iPFS for the cohort were 27.7 months (95% CI, 19.7-36.8) and 22.1 months (95% CI, 16.8-48.9), respectively. Lesion-level local control at 12 and 24 months was 89.9% and 87.5%, respectively. In a multivariable Cox regression model, inferior OS was associated with coalterations in KEAP1 and STK11 (hazard ratio [HR], 1.94; 95% CI, 1.04-3.62; q = 0.087), progressive (HR, 3.41; 95% CI, 1.38-8.39; q = 0.087), and mixed response (HR, 3.52; 95% CI, 1.2-10.3; q = 0.092) extracranial disease, and 6 or more BMs at time of diagnosis (HR, 2.58; 95% CI, 1.22-6.63; q = 0.087). Positive programmed death ligand 1 status was associated with improved OS (HR, 0.57; 95% CI, 0.37-0.87; P = .01). Inferior iPFS was associated with chemotherapy before SRS (HR, 2.69; 95% CI, 1.42-5.09; q = 0.04) and age >65 years (HR, 2.21; 95% CI, 1.25-3.93; q = 0.055). KRAS G12C was not associated with differences in iPFS, OS, or type of intracranial progression event following SRS.

CONCLUSIONS

Coalteration of KRAS and KEAP1/STK11 was associated with inferior OS, but not iPFS. Similar outcomes were found in patients harboring KRAS G12C and non-G12C mutant non-small cell lung cancer BMs. Further understanding of molecularly characterized subgroups will be critical in driving personalized radiation therapy for patients with lung cancer BMs.

STK11 mutations correlate with poor prognosis for advanced NSCLC treated with first-line immunotherapy or chemo-immunotherapy according to KRAS, TP53, KEAP1, and SMARCA4 status

BACKGROUND

The upfront treatment of non-oncogene-addicted NSCLC relies on immunotherapy alone (ICI) or in combination with chemotherapy (CT-ICI). Genomic aberrations such as KRAS, TP53, KEAP1, SMARCA4, or STK11 may impact survival outcomes.

METHODS

We performed an observational study of 145 patients treated with first-line IO or CT-ICI for advanced non-squamous (nsq) NSCLC at our institution tested with an extensive lab-developed NGS panel. The primary objective was to assess the clinical outcomes of STK11-mutated patients. Then, we performed an external validation through the public OAK/POPLAR dataset, including nsq NSCLC patients treated with single-agent ICI or CT.

RESULTS

Most patients were male (59.7 %), former smokers (61.1 %), with ECOG PS 0-1 (84 %), and received first-line CT-IO (58.6 %). 44.8 % had a mutation in KRAS, 21.4 % in KEAP1, 50.3 % in TP53, 13.1 % in SMARCA4, and 14.4 % in the STK11 gene. The mOS was 8 mo. (95 % CI, 5-16.7) for STK11 mutated pts and 17.3 mo. for STK11 wild-type patients (95 % CI, 8.9-24.4) (p = 0.038). TP53 (8.3 vs 17.3), KRAS (9.2 vs 15.9), and KEAP1 (8.9 vs 15.9) mutated patients evidenced a trend for dismal mOS. SMARCA4 status had no impact on mOS. STK11 mutations were detrimental to OS in the univariate (HR 1.74, p = 0.041) and multivariate model (HR 1.97, p = 0.025) after adjusting for sex, age, ECOG PS, treatment (ICI vs CT-ICI), KRAS, KEAP1, TP53, and SMARCA4 status. Genomic alterations did not impact the mPFS in our cohort. Within the OAK/POPLAR dataset, STK11 mutations (60/818 pts) were significantly associated with increased death risk in the univariate (HR 2.01, p < 0.001) and multivariate model (HR 1.66, p = 0.001) after adjusting for age, sex, treatment (ICI vs CT), KRAS, KEAP1, TP53, and SMARCA4 status.

CONCLUSION

STK11 aberrations hampered the mOS of nsq NSCLC patients treated with first-line ICI or CT-ICI. The negative prognostic impact seems to be unrelated to ICI administration.

Antithetical impacts of deleterious LRP1B mutations in non-squamous and squamous NSCLCs on predicting benefits from immune checkpoint inhibitor alone or with chemotherapy over chemotherapy alone: retrospective analyses of the POPLAR/OAK and CHOICE-01 trials

In non-small cell lung cancers, the non-squamous and squamous subtypes (nsqNSCLC and sqNSCLC) exhibit disparities in pathophysiology, tumor immunology, and potential genomic correlates affecting responses to immune checkpoint inhibitor (ICI)-based treatments. In our in-house training cohort (n=85), the presence of the LRP1B deleterious mutation (LRP1B-del) was associated with longer and shorter progression-free survival (PFS) on ICIs alone in nsqNSCLCs and sqNSCLCs, respectively (Pinteraction=0.008). These results were validated using a larger public ICI cohort (n=208, Pinteraction<0.001). Multiplex immunofluorescence staining revealed an association between LRP1B-del and increased and decreased numbers of tumor-infiltrating CD8+ T cells in nsqNSCLCs (P=0.040) and sqNSCLCs (P=0.014), respectively. In the POPLAR/OAK cohort, nsqNSCLCs with LRP1B-del demonstrated improved PFS benefits from atezolizumab over docetaxel (hazard ratio (HR) =0.70, P=0.046), whereas this benefit was negligible in those without LRP1B-del (HR=1.05, P=0.64). Conversely, sqNSCLCs without LRP1B-del benefited more from atezolizumab (HR=0.60, P=0.002) than those with LRP1B-del (HR=1.30, P=0.31). Consistent results were observed in the in-house CHOICE-01 cohort, in which nsqNSCLCs with LRP1B-del and sqNSCLCs without LRP1B-del benefited more from toripalimab plus chemotherapy than from chemotherapy alone (Pinteraction=0.008). This multi-cohort study delineates the antithetical impacts of LRP1B-del in nsqNSCLCs and sqNSCLCs on predicting the benefits from ICI alone or with chemotherapy over chemotherapy alone. Our findings highlight the distinct clinical utility of LRP1B-del in guiding treatment choices for nsqNSCLCs and sqNSCLCs, emphasizing the necessity for a detailed analysis based on pathological subtypes when investigating biomarkers for cancer therapeutics.

Biomarkers for immunotherapy resistance in non-small cell lung cancer

Immunotherapy has revolutionised the treatment landscape of non-small cell lung cancer (NSCLC), significantly improving survival outcomes and offering renewed hope to patients with advanced disease. However, the majority of patients experience limited long-term benefits from immune checkpoint inhibition (ICI) due to the development of primary or acquired immunotherapy resistance. Accurate predictive biomarkers for immunotherapy resistance are essential for individualising treatment strategies, improving survival outcomes, and minimising potential treatment-related harm. This review discusses the mechanisms underlying resistance to immunotherapy, addressing both cancer cell-intrinsic and cancer cell-extrinsic resistance processes. We summarise the current utility and limitations of two clinically established biomarkers: programmed death ligand 1 (PD-L1) expression and tumour mutational burden (TMB). Following this, we present a comprehensive review of emerging immunotherapy biomarkers in NSCLC, including tumour neoantigens, epigenetic signatures, markers of the tumour microenvironment (TME), genomic alterations, host-microbiome composition, and circulating biomarkers. The potential clinical applications of these biomarkers, along with novel approaches to their biomarker identification and targeting, are discussed. Additionally, we explore current strategies to overcome immunotherapy resistance and propose incorporating predictive biomarkers into an adaptive clinical trial design, where specific immune signatures guide subsequent treatment selection.

Next-generation immunotherapy: igniting new hope for lung cancer

Adoption of immunotherapy has completely transformed the treatment landscape of cancer. Patients with advanced cancer treated with immunotherapy may benefit from durable tumor response and long-term survival. The most widely used immunotherapy in solid tumors is anti-programmed-death (ligand) protein (PD-(L)1), which is now an integral part of non-small cell lung cancer (NSCLC) treatment irrespective of histological cell types and tumor stage. However, the vast majority of patients with advanced NSCLC treated with anti-PD-(L)1 still develop therapeutic resistance, and the prognosis after anti-PD-(L)1 resistance is poor. Resistance mechanisms to PD-1 blockade are often complex and encompass a combination of defects within the cancer-immunity cycle. These defects include failure in antigen presentation and T-cell priming, presence of co-inhibitory immune checkpoints, inability of immune cells to infiltrate the tumor, and presence of immunosuppressive tumor microenvironment. Recently, advances in drug design, genomic sequencing, and gene editing technologies have led to development of next-generation immunotherapies that may potentially overcome these resistance mechanisms. In this review, we will discuss the anti-PD-(L)1 resistance mechanism landscape in NSCLC and four novel modalities of immunotherapy in detail, namely novel immune checkpoint inhibitor and targeted therapy combinations, bispecific antibodies, cancer vaccine, and cell therapy. These novel therapeutics have all demonstrated early clinical data in NSCLC treatment and may work synergistically with each other to restore anticancer immunity. In addition, we share our perspectives on the future promises and challenges in the transformation of these novel immunotherapies to standard clinical care.

SMARCA4 mutations and expression in lung adenocarcinoma: prognostic significance and impact on the immunotherapy response

The switch/sucrose non-fermenting (SWI/SNF) complex family includes important chromatin-remodeling factors that are frequently mutated in lung adenocarcinoma (LUAD). However, the role of one family member, SMARCA4, in LUAD prognosis and immunotherapy sensitivity remains unclear. In the present study, 6745 LUAD samples from the cBioPortal database were used to analyze the relationships between SMARCA4 mutations and patient prognoses and clinical characteristics. Additionally, we examined the correlation between SMARCA4 mutations and prognosis in patients treated with immunotherapy using two immune-related datasets. SMARCA4 mutations and low expression were associated with shorter survival, and mutations were associated with a high tumor mutational burden and high microsatellite instability. SMARCA4 mutations were accompanied by KRAS, KEAP1, TP53 and STK11 mutations. No significant difference was observed in the immunotherapy response between patients with and without SMARCA4 mutations. When KRAS or STK11 mutations were present, immunotherapy effectiveness was poorer; however, when both SMARCA4 and TP53 mutations were present, immunotherapy was more effective. Furthermore, low SMARCA4 expression predicted a higher immunophenoscore, and SMARCA4 expression was correlated with certain immune microenvironment features. Taken together, our results suggest that SMARCA4 mutations and low expression might be associated with poor LUAD prognosis. Additionally, immunotherapy efficacy in patients with SMARCA4 mutations depended on the co-mutant genes. Thus, SMARCA4 could be an important factor to be considered for LUAD diagnosis and treatment.

A nomogram for cancer-specific survival of lung adenocarcinoma patients: A SEER based analysis

Background

Non-small cell lung cancer (NSCLC) accounts for 85 % of lung cancer cases. Among NSCLC subtypes, lung adenocarcinoma (LUAD) stands as the most prevalent. Regrettably, LUAD continues to exhibit a notably unfavorable overall prognosis. This study's primary aim was to develop and validate prognostic tools capable of predicting the likelihood of cancer-specific survival (CSS) in patients with LUAD.

Methods

We retrospectively collected 21,099 patients diagnosed with LUAD between 2010 and 2015, and 8290 patients diagnosed between 2004 and 2009 from SEER database. The cohort of 21,099 patients served as the prognostic group for the exploration of LUAD-related prognostic risk factors. The cohort of 8290 patients was designated for external validation. We created a training set and an internal validation set in the prognostic group for the development and internal validation of CSS nomograms. CSS predictors were identified through the least absolute shrinkage and selection operator (Lasso) regression analysis. Prognostic model was constructed via Cox hazard regression analysis, presented in the form of both static and dynamic network-based nomograms.

Results

Several independent prognostic factors were incorporated into the construction of nomogram. The nomogram accurately predicted CSS at 1, 3, and 5 years, with respective AUC values of 0.769, 0.761, and 0.748 for the training group, and 0.741, 0.752, and 0.740 for the testing group. The study demonstrated a strong agreement between anticipated and actual CSS values, supported by decision curve analysis (DCA) and time-dependent calibrated curves. High-risk patients based on the nomogram exhibiting significantly lower survival rates compared to their low-risk counterparts according to Kaplan-Meier (K-M) curves. The nomogram demonstrates excellent predictive power in the external validation cohort.

Conclusions

A dependable and user-friendly nomogram has been developed, available in both static and online dynamic calculator formats, to facilitate healthcare professionals in accurately estimating the likelihood of CSS for patients diagnosed LUAD.

Opportunities and challenges of using circulating tumor DNA to predict lung cancer immunotherapy efficacy

Immune checkpoint inhibitors (ICIs), particularly anti-programmed death 1 (PD-1)/ programmed death ligand 1 (PD-L1) antibodies, have led to significant progress in lung cancer treatment. However, only a minority of patients have responses to these therapies. Detecting peripheral blood of circulating tumor DNA (ctDNA) allows minimally invasive diagnosis, characterization, and monitoring of lung cancer. ctDNA has potential to be a prognostic biomarker and a predictor of the response to ICI therapy since it can indicate the genomic status and tumor burden. Recent studies on lung cancer have shown that pretreatment ctDNA analysis can detect residual proliferative disease in the adjuvant immunotherapy setting and evaluate tumor burden in patients with metastatic disease. Early ctDNA dynamics can not only predict the clinical outcome of ICI therapy but also help distinguish between pseudoprogression and real progression. Furthermore, in addition to quantitative assessment, ctDNA can also detect genetic predictors of response to ICI therapy. However, barriers still exist in the application of ctDNA analysis in clinical lung cancer treatment. The predictive value of ctDNA in lung cancer immunotherapy requires further identification and resolution of these challenges. This review aims to summarize the existing data of ctDNA analysis in patients receiving immunotherapy for lung cancer, understand the limitations of clinical treatment, and discuss future research directions.

RAS signaling in carcinogenesis, cancer therapy and resistance mechanisms

Variants in the RAS family (HRAS, NRAS and KRAS) are among the most common mutations found in cancer. About 19% patients with cancer harbor RAS mutations, which are typically associated with poor clinical outcomes. Over the past four decades, KRAS has long been considered an undruggable target due to the absence of suitable small-molecule binding sites within its mutant isoforms. However, recent advancements in drug design have made RAS-targeting therapies viable, particularly with the approval of direct KRASG12C inhibitors, such as sotorasib and adagrasib, for treating non-small cell lung cancer (NSCLC) with KRASG12C mutations. Other KRAS-mutant inhibitors targeting KRASG12D are currently being developed for use in the clinic, particularly for treating highly refractory malignancies like pancreatic cancer. Herein, we provide an overview of RAS signaling, further detailing the roles of the RAS signaling pathway in carcinogenesis. This includes a summary of RAS mutations in human cancers and an emphasis on therapeutic approaches, as well as de novo, acquired, and adaptive resistance in various malignancies.

Surgical resection following chemoradiotherapy for thoracic SMARCA4-deficient undifferentiated tumor: a report of two cases

BACKGROUND

Thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4-UT) is a high-grade malignant neoplasm with a poor prognosis. Most cases of SMARCA4-UT have extensive chest wall and mediastinum involvement. The efficacy of surgical resection has not been clearly established. Here, we report two surgical cases of SMARCA4-UT with chest wall invasion after chemoradiotherapy.

CASE PRESENTATION

The first patient was a 40-year-old man with back pain. Computed tomography revealed a 6.8 cm mass in contact with the thoracic vertebrae near the intervertebral foramen, which was suspected to involve the third to fifth ribs. The patient was diagnosed with SMARCA4-UT with clinical T3N0M0 stage IIB. The tumor shrank after chemoradiotherapy, and conversion surgery combined with partial vertebrectomy was performed. Histopathological findings revealed 30% residual tumor in the tumor bed. Thirty-six days after surgery, the patient developed multiple liver metastases and peritoneal dissemination. Chemotherapy combined with immune checkpoint inhibitor treatment was performed, resulting in tumor shrinkage. However, peritoneal dissemination recurred within a short interval. The patient died 5 months postoperatively. The second patient was a 74-year-old man with chest pain. Computed tomography revealed a 7.4-cm mass in the left upper lobe with invasion of the third and fourth ribs. The patient was initially diagnosed with non-small cell lung cancer with clinical T4N1M0 stage IIIA. The tumor shrank after induction chemoradiotherapy, and a left upper lobectomy combined with the chest wall resection was performed. Based on histopathological findings, the patient was diagnosed with SMARCA4-UT. The residual tumor percentage was 3%. The patient was followed up for 12 months postoperatively without recurrence.

CONCLUSIONS

We performed the complete resection of SMARCA4-UT following chemoradiotherapy. The two surgical cases had different postoperative courses. Radical surgery after chemoradiotherapy is effective for local control. However, its long-term prognostic efficacy remains unclear. Multidisciplinary approaches and further investigations of novel therapeutic options are required.

The Complex Roles of Redox and Antioxidant Biology in Cancer

Redox reactions control fundamental biochemical processes, including energy production, metabolism, respiration, detoxification, and signal transduction. Cancer cells, due to their generally active metabolism for sustained proliferation, produce high levels of reactive oxygen species (ROS) compared to normal cells and are equipped with antioxidant defense systems to counteract the detrimental effects of ROS to maintain redox homeostasis. The KEAP1-NRF2 system plays a major role in sensing and regulating endogenous antioxidant defenses in both normal and cancer cells, creating a bivalent contribution of NRF2 to cancer prevention and therapy. Cancer cells hijack the NRF2-dependent antioxidant program and exploit a very unique metabolism as a trade-off for enhanced antioxidant capacity. This work provides an overview of redox metabolism in cancer cells, highlighting the role of the KEAP1-NRF2 system, selenoproteins, sulfur metabolism, heme/iron metabolism, and antioxidants. Finally, we describe therapeutic approaches that can be leveraged to target redox metabolism in cancer.

NRF2 Signaling Pathway in Chemo/Radio/Immuno-Therapy Resistance of Lung Cancer: Looking Beyond the Tip of the Iceberg

Lung cancer is one of the most common causes of cancer death in men and women worldwide. Various combinations of surgery, chemotherapy, radiation therapy and immunotherapy are currently used to treat lung cancer. However, the prognosis remains relatively poor due to the higher frequency of tumor mutational burden (TMB). Nuclear factor E2-related factor 2 (NFE2L2/NRF2) is often considered a primary regulator of the expression of antioxidant enzymes and detoxification proteins and is involved in cytoprotection. On the contrary, NRF2 is even known to induce metastasis and support tumor progression. Kelch-like ECH-associated protein 1 (KEAP1) plays an important role in negatively regulating NRF2 activity via CUL3-mediated ubiquitinylation and successive proteasomal degradation. Extensive research has shown that the genetic alterations of KEAP1/NFE2L2/CUL3 genes lead to increased expression of NRF2 and its target genes in lung cancer. Thus, these studies provide ample evidence for the dual role of NRF2 in lung cancer. In this review, we discussed the mechanistic insights into the role of NRF2 signaling in therapy resistance by focusing on cell lines, mouse models, and translational studies in lung cancer. Finally, we highlighted the potential therapeutic strategies targeting NRF2 inhibition, followed by the discussion of biomarkers related to NRF2 activity in lung cancer. Overall, our article exclusively discusses in detail the NRF2 signaling pathway in resistance to therapy, especially immunotherapy, and its therapeutic avenue in the treatment of lung cancer.

AI-powered genomic mutation signature for predicting immune checkpoint inhibitor therapy outcomes in gastroesophageal cancer: a multi-cohort analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) have significantly transformed the treatment of gastroesophageal cancer (GEC). However, the lack of reliable prognostic biomarkers hinders the ability to predict patient response to ICI therapy.

METHODS

In this study, we engineered and validated a genomic mutation signature (GMS) utilizing an innovative artificial intelligence (AI) algorithm to forecast ICI therapy outcomes in GEC patients. We further explored immune profiles across subtypes through comprehensive multiomics analysis. Our investigation of drug sensitivity data from the Genomics of Drug Sensitivity in Cancer (GDSC) database led to the identification of trametinib as a potential therapeutic agent. We subsequently evaluated trametinib's efficacy in AGS and MKN45 cell lines using Cell Counting Kit-8 (CCK8) assays and clonogenic experiments.

RESULTS

We developed a GMS by integrating 297 algorithms, enabling autonomous prognosis prediction for GEC patients. The GMS demonstrated consistent performance across three public cohorts, exhibiting high sensitivity and specificity for overall survival (OS) at 6, 12, and 18 months, as shown by Receiver Operator Characteristic Curve (ROC) analysis. Notably, the GMS surpassed traditional clinical and molecular features, including tumor mutational burden (TMB), programmed death-ligand 1 (PD-L1) expression, and microsatellite instability (MSI), in predictive accuracy. Low-risk samples exhibited elevated levels of cytolytic immune cells and heightened immunogenic potential compared to high-risk samples. Our investigation identified trametinib as a potential therapeutic agent. An inverse correlation was observed between GMS and trametinib IC50. Moreover, the high-risk-derived AGS cell line showed increased sensitivity to trametinib compared to the low-risk-derived MKN45 cell line.

CONCLUSION

The GMS utilized in this study successfully demonstrated the ability to reliably predict the survival advantage for patients with GECs undergoing ICI therapy.

AXL expression reflects tumor-immune cell dynamics impacting outcome in non-small cell lung cancer patients treated with immune checkpoint inhibitor monotherapy

Introduction

AXL receptor expression is proposed to confer immune-checkpoint inhibitor (ICI)-resistance in non-small cell lung cancer (NSCLC) patients. We sought to interrogate AXL expression in conjunction with mutational and tumor-microenvironmental features to uncover predictive mechanisms of resistance in ICI-treated NSCLC patients.

Methods

Tumor samples from 111 NSCLC patients treated with ICI-monotherapy were analyzed by immunohistochemistry for tumor- and immune-AXL expression. Subsets of patients were analyzed by whole-exome sequencing (n = 44) and imaging mass cytometry (n = 14). Results were related to ICI-outcome measurements.

Results

Tumor-cell AXL expression correlated with aggressive phenotypic features including reduced OS in patients treated with ICIs (P = 0.04) after chemotherapy progression, but conversely associated with improved disease control (P = 0.045) in ICI-treated, PD-L1 high first-line patients. AXL+ immune-cell infiltration correlated with total immune-cell infiltration and improved overall outcomes (PFS: P = 0.044, OS: P = 0.054). Tumor-cell AXL-upregulation showed enrichment in mutations associated with PD-L1-upregulation and ICI-response such as MUC4 and ZNF469, as well as adverse mutations including CSMD1 and LRP1B which associated with an immune-suppressed tumor phenotype and poor ICI prognosis particularly within chemotherapy-treated patients. Tumor mutational burden had no effect on ICI-outcomes and was associated with a lack of tumor-infiltrating immune cells. Spatial-immunophenotyping provided evidence that tumor-cell AXL-upregulation and adverse mutations modulate the tumor microenvironment in favor of infiltrating, activated neutrophils over anti-tumor immune-subsets including CD4 and CD8 T-cells.

Conclusion

Tumor-cell AXL-upregulation correlated with distinct oncotypes and microenvironmental immune-profiles that define chemotherapy-induced mechanisms of ICI-resistance, which suggests the combination of AXL inhibitors with current chemoimmunotherapy regimens can benefit NSCLC patients.

Effects of KRAS, STK11, KEAP1, and TP53 mutations on the clinical outcomes of immune checkpoint inhibitors among patients with lung adenocarcinoma

BACKGROUND

This study aimed to identify the associations between individual KRAS, STK11, KEAP1, or TP53 mutations, as well as the comutation status of these genes, and the tumor mutation burden (TMB) with clinical outcomes of lung adenocarcinoma patients treated with immune checkpoint inhibitors (ICIs).

METHODS

We collected data from patients with lung adenocarcinoma treated with ICIs from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database between June 2019 and August 2023. The main endpoints were the treatment response and overall survival (OS).

RESULTS

Among 343 patients with lung adenocarcinoma, 61 (18%), 69 (20%), 41 (12%), and 222 (65%) patients had KRAS, STK11, KEAP1, and TP53 mutations, respectively. An overall objective response was observed in 94 of 338 patients (28%), including 2 (1%) who achieved a complete response and 92 (27%) who achieved a partial response. Patients with STK11, KEAP1, or TP53 mutations had a significantly greater TMB (P<0.001). According to the univariate analysis, the treatment response was significantly correlated with TP53 mutation in both the general (P = 0.041) and KRAS wild-type (P = 0.009) populations. KEAP1 and TP53 mutations were associated with worse OS among assessable patients (hazard ratio (HR) = 2.027, P = 0.002; HR = 1.673, P = 0.007, respectively) and among patients without KRAS mutations (HR = 1.897, P = 0.012; HR = 1.908, P = 0.004, respectively). According to the multivariate analysis, KEAP1 (HR = 1.890, P = 0.008) and TP53 (HR = 1.735, P = 0.011) mutations were found to be independent factors for OS.

CONCLUSIONS

STK11, KEAP1, and TP53 mutations are significantly associated with a high TMB. TP53 mutation could affect the treatment response to some degree, and both KEAP1 and TP53 mutations resulted in inferior OS in the general patient population and in those with KRAS-wild-type lung adenocarcinoma, indicating that KEAP1 and TP53 mutations might act as prognostic factors for ICI treatment in lung adenocarcinoma patients.

Uncovering molecular features driving lung adenocarcinoma heterogeneity in patients who formerly smoked

BACKGROUND

An increasing proportion of lung adenocarcinoma (LUAD) occurs in patients even after they have stopped smoking. Here, we aimed to determine whether tobacco smoking induced changes across LUADs from patients who formerly smoked correspond to different biological and clinical factors.

METHODS

Random forest models (RFs) were trained utilizing a smoking associated signature developed from differentially expressed genes between LUAD patients who had never smoked (NS) or currently smoked (CS) from TCGA (n = 193) and BCCA (n = 69) cohorts. The RFs were subsequently applied to 299 and 131 formerly smoking patients from TCGA and MSKCC cohorts, respectively. FS were RF-classified as either CS-like or NS-like and associations with patient characteristics, biological features, and clinical outcomes were determined.

RESULTS

We elucidated a 123 gene signature that robustly classified NS and CS in both RNA-seq (AUC = 0.85) and microarray (AUC = 0.92) validation test sets. The RF classified 213 patients who had formerly smoked as CS-like and 86 as NS-like from the TCGA cohort. CS-like and NS-like status in formerly smoking patients correlated poorly with patient characteristics but had substantially different biological features including tumor mutational burden, number of mutations, mutagenic signatures and immune cell populations. NS-like formerly smoking patients had 17.5 months and 18.6 months longer overall survival than CS-like patients from the TCGA and MSKCC cohorts, respectively.

CONCLUSIONS

Patients who had formerly smoked with LUAD harbor heterogeneous tumor biology. These patients can be divided by smoking induced gene expression to inform prognosis and underlying biological characteristics for treatment selection.

A Critical Review of the Impact of SMARCA4 Mutations on Survival Outcomes in Non-Small Cell Lung Cancer

This critical review investigates the impact of SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 4 (SMARCA4) mutations on survival outcomes in non-small cell lung cancer (NSCLC) through an analysis of 21 peer-reviewed articles. Survival analyses across this review demonstrated consistently worse outcomes for SMARCA4-mutated vs. SMARCA4 wild-type NSCLC patients, specifically emphasizing class 1 truncating mutations as an independent factor for poor overall survival. In addition, this review explores the clinicopathologic characteristics of SMARCA4 mutations and their impact on various treatment modalities, including immune checkpoint inhibitors (ICIs) both with and without Kirsten rat sarcoma viral oncogene homolog (KRAS) co-mutations. The potential ineffectiveness of ICI treatment in NSCLC is explored through the impact of SMARCA4/KRAS co-mutations on the tumor microenvironment. Moreover, this NSCLC review consistently reported statistically worse overall survival outcomes for SMARCA4/KRAS co-mutations than SMARCA4 wild-type/KRAS-mutated cohorts, extending across ICIs, chemo-immunotherapy (CIT), and KRAS G12C inhibitors. Designing prospective clinical SMARCA4-mutated or SMARCA4/KRAS co-mutated NSCLC trials to evaluate targeted therapies and immunotherapy may lead to a better understanding of how to improve cancer patients' outcomes and survival rates.

SMARCA4 alterations in non-small cell lung cancer: a systematic review and meta-analysis

AIMS

A mutation in the SMARCA4 gene which encodes BRG1, a common catalytic subunit of switch/sucrose non-fermentable chromatin-remodelling complexes, plays a vital role in carcinogenesis. SMARCA4 mutations are present in approximately 10% of non-small cell lung cancers (NSCLC), making it a crucial gene in NSCLC, but with varying prognostic associations. To explore this, we conducted a systematic review and meta-analysis on the prognostic significance of SMARCA4 mutations in NSCLC.

METHODS

Electronic database search was performed from inception to December 2022. Study characteristics and prognostic data were extracted from each eligible study. Depending on heterogeneity, pooled HR and 95% CI were derived using the random-effects or fixed-effects models.

RESULTS

8 studies (11 cohorts) enrolling 8371 patients were eligible for inclusion. Data on overall survival (OS) and progression-free survival (PFS) were available from 8 (10 cohorts) and 1 (3 cohorts) studies, respectively. Comparing SMARCA4-mutated NSCLC patients with SMARCA4-wild-type NSCLC patients, the summary HRs for OS and PFS were 1.49 (95% CI 1.18 to 1.87; I2=84%) and 3.97 (95% CI 1.32 to 11.92; I2=79%), respectively. The results from the trim-and-fill method for publication bias and sensitivity analysis were inconsistent with the primary analyses. Three studies reported NSCLC prognosis for category I and II mutations separately; category I was significantly associated with OS.

CONCLUSION

Our findings suggest that SMARCA4 mutation negatively affects NSCLC OS and PFS. The prognostic effects of SMARCA4-co-occurring mutations and the predictive role of SMARCA4 mutation status in immunotherapy require further exploration.

Prevalence and Associations of Co-occurrence of NFE2L2 Mutations and Chromosome 3q26 Amplification in Lung Cancer

Background   NFE2L2 (nuclear factor erythroid-2-related factor-2) encodes a basic leucine zipper (bZIP) transcription factor and exhibits variations in various tumor types, including lung cancer. In this study, we comprehensively investigated the impact of simultaneous mutations on the survival of NFE2L2 -mutant lung cancer patients within specific subgroups. Methods  A cohort of 1,103 lung cancer patients was analyzed using hybridization capture-based next-generation sequencing. Results  The NFE2L2 gene had alterations in 3.0% (33/1,103) of lung cancer samples, including 1.5% (15/992) in adenocarcinoma and 16.2% (18/111) in squamous cell carcinoma. Thirty-four variations were found, mainly in exons 2 (27/34). New variations in exon 2 (p.D21H, p.V36_E45del, p.F37_E45del, p.R42P, p.E67Q, and p.L76_E78delinsQ) were identified. Some patients had copy number amplifications. Co-occurrence with TP53 (84.8%), CDKN2A (33.3%), KMT2B (33.3%), LRP1B (33.3%), and PIK3CA (27.3%) mutations was common. Variations of NFE2L2 displayed the tightest co-occurrence with IRF2 , TERC , ATR , ZMAT3 , and SOX2 ( p  < 0.001). In The Cancer Genome Atlas Pulmonary Squamous Carcinoma project, patients with NFE2L2 variations and 3q26 amplification had longer median survival (63.59 vs. 32.04 months, p  = 0.0459) and better overall survival. Conclusions   NFE2L2 mutations display notable heterogeneity in lung cancer. The coexistence of NFE2L2 mutations and 3q26 amplification warrants in-depth exploration of their potential clinical implications and treatment approaches for affected patients.

Immune checkpoint blockade resistance in lung cancer: emerging mechanisms and therapeutic opportunities

Immune checkpoint blockade (ICB) therapy works by inhibiting suppressive checkpoints that become upregulated after T cell activation, like PD-1/PD-L1 and CTLA-4. While the initial FDA approvals of ICB have revolutionized cancer therapies and fueled a burgeoning immuno-oncology field, more recent clinical development of new agents has been slow. Here, focusing on lung cancer, we review the latest research uncovering tumor cell intrinsic and extrinsic ICB resistance mechanisms as major hurdles to treatment efficacy and clinical progress. These include genomic and non-genomic tumor cell alterations, along with host and microenvironmental factors like the microbiome, metabolite accumulation, and hypoxia. Together, these factors can cooperate to promote immunosuppression and ICB resistance. Opportunities to prevent resistance are constantly evolving in this rapidly expanding field, with the goal of moving toward personalized immunotherapeutic regimens.

Targeting KRASG12C in Non-Small-Cell Lung Cancer: Current Standards and Developments

Among the most common molecular alterations detected in non-small-cell lung cancer (NSCLC) are mutations in Kristen Rat Sarcoma viral oncogene homolog (KRAS). KRAS mutant NSCLC is a heterogenous group of diseases, different from other oncogene-driven tumors in terms of biology and response to therapies. Despite efforts to develop drugs aimed at inhibiting KRAS or its signaling pathways, KRAS had remained undruggable for decades. The discovery of a small pocket in the binding switch II region of KRASG12C has revolutionized the treatment of KRASG12C-mutated NSCLC patients. Sotorasib and adagrasib, direct KRASG12C inhibitors, have been approved by the US Food and Drug Administration (FDA) and other regulatory agencies for patients with previously treated KRASG12C-mutated NSCLC, and these advances have become practice changing. However, first-line treatment in KRASG12C-mutated NSCLC does not differ from NSCLC without actionable driver genomic alterations. Treatment with KRASG12C inhibitors is not curative and patients develop progressive disease, so understanding associated mechanisms of drug resistance is key. New KRASG12C inhibitors and several combination therapy strategies, including with immune checkpoint inhibitors, are being studied in clinical trials. The aim of this review is to explore the clinical impact of KRAS, and outline different treatment approaches, focusing on the novel treatment of KRASG12C-mutated NSCLC.

TP53 co-mutations in advanced lung adenocarcinoma: comparative bioinformatic analyses suggest ambivalent character on overall survival alongside KRAS, STK11 and KEAP1 mutations

Background

Recently, we could show that the co-mutations of KRAS + KEAP1, STK11 + KEAP1 and KRAS + STK11 + KEAP1 lead to a significantly shorter median overall survival (mOS) across treatments by analyzing multiple datasets. TP53, a tumor suppressor gene, plays a crucial role in regulating cell cycle progression. Its mutations occur in approximately 40-50% of non-small lung cancer (NSCLC). Co-occurrence of all four mentioned mutations has been a matter of debate for years. The aim of this study was to assess the distribution of these four mutations and the influence of the different co-mutational patterns on survival.

Methods

We present a comparative bioinformatic analysis and refer to data of 4,109 patients with lung adenocarcinoma (LUAD).

Results

Most of the mutations within the LUAD belong to TP53-only (29.0%), quadruple-negative (25.9%) and KRAS-only (13.4%). Whereas TP53-mutations seem to have protective effects in the context of further KEAP1- and KRAS + KEAP1-alterations (improved mOS), their role seems contrary if acquired in an already existing combination of mutations as KRAS + STK11, KRAS + STK11 + KEAP1 and STK1 + KEAP1. TP53 co-mutationshad a negative influence on KRAS-only mutated LUAD (mOS reduced significantly by more than 30%).

Discussion

These data underline the need for complex mutational testing to estimate prognosis more accurately in patients with advanced LUAD.

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

Tumor immune microenvironment (TIME) and its indications for lung cancer patient prognosis and therapeutic response have become new hotspots in cancer research in recent years. Tumor cells, immune cells, various regulatory factors, and their interactions in the TIME have been suggested to commonly influence lung cancer development and therapeutic outcome. The heterogeneity of TIME is composed of dynamic immune-related components, including various cancer cells, immune cells, cytokine/chemokine environments, cytotoxic activity, or immunosuppressive factors. The specific composition of cell subtypes may facilitate or hamper the response to immunotherapy and influence patient prognosis. Various markers have been found to stratify the patient prognosis or predict the therapeutic outcome. In this article, we systematically reviewed the recent advancement of TIME studies in lung adenocarcinoma (LUAD) using single-cell RNA sequencing (scRNA-seq) techniques, with specific focuses on the roles of TIME in LUAD development, TIME heterogeneity, indications of TIME in patient prognosis and therapeutic response during immunotherapy and drug resistance. The main findings in TIME heterogeneity and relevant markers or models for prognosis stratification and response prediction have been summarized. We hope that this review provides an overview of TIME status in LUAD and an inspiration for future development of strategies and biomarkers in LUAD treatment.

Emerging Therapies in Kirsten Rat Sarcoma Virus (+) Non-Small-Cell Lung Cancer

Kirsten rat sarcoma virus (KRAS) is the most frequently found oncogene in human cancers, including non-small-cell lung cancer (NSCLC). For many years, KRAS was considered "undruggable" due to its structure and difficult targeting. However, the discovery of the switch II region in the KRAS-G12C-mutated protein has changed the therapeutic landscape with the design and development of novel direct KRAS-G12C inhibitors. Sotorasib and adagrasib are FDA-approved targeted agents for pre-treated patients with KRAS-G12C-mutated NSCLC. Despite promising results, the efficacy of these novel inhibitors is limited by mechanisms of resistance. Ongoing studies are evaluating combination strategies for overcoming resistance. In this review, we summarize the biology of the KRAS protein and the characteristics of KRAS mutations. We then present current and emerging therapeutic approaches for targeting KRAS mutation subtypes intending to provide individualized treatment for lung cancer harboring this challenging driver mutation.

Redoxhigh phenotype mediated by KEAP1/STK11/SMARCA4/NRF2 mutations diminishes tissue-resident memory CD8+ T cells and attenuates the efficacy of immunotherapy in lung adenocarcinoma

Metabolism reprogramming within the tumor microenvironment (TME) can have a profound impact on immune cells. Identifying the association between metabolic phenotypes and immune cells in lung adenocarcinoma (LUAD) may reveal mechanisms of resistance to immune checkpoint inhibitors (ICIs). Metabolic phenotypes were classified by expression of metabolic genes. Somatic mutations and transcriptomic features were compared across the different metabolic phenotypes. The metabolic phenotype of LUAD is predominantly determined by reductase-oxidative activity and is divided into two categories: redoxhigh LUAD and redoxlow LUAD. Genetically, redoxhigh LUAD is mainly driven by mutations in KEAP1, STK11, NRF2, or SMARCA4. These mutations are more prevalent in redoxhigh LUAD (72.5%) compared to redoxlow LUAD (17.4%), whereas EGFR mutations are more common in redoxlow LUAD (19.0% vs. 0.7%). Single-cell RNA profiling of pre-treatment and post-treatment samples from patients receiving neoadjuvant chemoimmunotherapy revealed that tissue-resident memory CD8+ T cells are responders to ICIs. However, these cells are significantly reduced in redoxhigh LUAD. The redoxhigh phenotype is primarily attributed to tumor cells and is positively associated with mTORC1 signaling. LUAD with the redoxhigh phenotype demonstrates a lower response rate (39.1% vs. 70.8%, p = 0.001), shorter progression-free survival (3.3 vs. 14.6 months, p = 0.004), and overall survival (12.1 vs. 31.2 months, p = 0.022) when treated with ICIs. The redoxhigh phenotype in LUAD is predominantly driven by mutations in KEAP1, STK11, NRF2, and SMARCA4. This phenotype diminishes the number of tissue-resident memory CD8+ T cells and attenuates the efficacy of ICIs.

Outcomes in patients treated with frontline immune checkpoint inhibition (ICI) for advanced NSCLC with KRAS mutations and STK11/KEAP1 comutations across PD-L1 levels

INTRODUCTION

In patients with advanced NSCLC (aNSCLC), the impact of KRAS mutations (m) and comutations with STK11 and KEAP1 on outcomes across different PD-L1 levels remains incompletely understood. We aimed to investigate the frequency of KRAS mutations and comutations across PD-L1 levels, and the association between these mutations and survival, stratified by PD-L1 expression.

METHODS

We conducted a nationwide cohort study of patients diagnosed with aNSCLC between 2016 and 2021 treated with frontline (chemo)immunotherapy, who underwent molecular genotyping including KRAS, STK11, and KEAP1. Real-world overall survival (OS) and progression-free survival (rwPFS) were estimated using Kaplan-Meier methodology. Cox multivariable regressions were used to evaluate the association between KRASm and survival across different PD-L1 strata, and to assess whether the association between KRASm and survival differed by PD-L1 level. Finally, within subgroups defined by PD-L1 expression, we used interaction terms to assess whether co-mutations with STK11 and KEAP1 moderated the association between KRAS mutation and survival.

RESULTS

Of our 2593-patient cohort, 982 (37.9 %) were KRASm and 1611 (62.1 %) KRASwt. KRASm were enriched in the PD-L1 ≥50 % cohort (334/743, 45 %), but within patients with KRASm, co-mutations with STK11 and KEAP1 were enriched in the PD-L1 0 % cohort. KRASm was associated with significantly worse OS in the PD-L1 0 % cohort compared to the PD-L1 ≥50 % cohort (P for interaction = 0.008). On adjusted analyses stratified by PD-L1, KRASm was associated with worse survival only in the PD-L1 0 % group (OS HR 1.46, p = 0.001). KEAP1 and STK11 comutations were most strongly associated with worse OS in the PD-L1 0 % subgroup; patients with triple KRASm/KEAPm/STK11m PD-L1 0 % NSCLC experienced the worst outcomes.

CONCLUSIONS

KRASm are associated with worse overall survival in PD-L1 negative NSCLC; however, this association is largely driven by comutations with STK11 and KEAP1, which are enriched in PD-L1 negative tumors.

Combining Genomic Biomarkers to Guide Immunotherapy in Non-Small Cell Lung Cancer

PURPOSE

The clinical value of STK11, KEAP1, and EGFR alterations for guiding immune checkpoint blockade (ICB) therapy in non-small cell lung cancer (NSCLC) remains controversial, as some patients with these proposed resistance biomarkers show durable ICB responses. More specific combinatorial biomarker approaches are urgently needed for this disease.

EXPERIMENTAL DESIGN

To develop a combinatorial biomarker strategy with increased specificity for ICB unresponsiveness in NSCLC, we performed a comprehensive analysis of 254 patients with NSCLC treated with ligand programmed death-ligand 1 (PD-L1) blockade monotherapy, including a discovery cohort of 75 patients subjected to whole-genome sequencing (WGS), and an independent validation cohort of 169 patients subjected to tumor-normal large panel sequencing. The specificity of STK11/KEAP1/EGFR alterations for ICB unresponsiveness was assessed in the contexts of a low (<10 muts/Mb) or high (≥10 muts/Mb) tumor mutational burden (TMB).

RESULTS

In low TMB cases, STK11/KEAP1/EGFR alterations were highly specific biomarkers for ICB resistance, with 0/15 (0.0%) and 1/34 (2.9%) biomarker-positive patients showing treatment benefit in the discovery and validation cohorts, respectively. This contrasted with high TMB cases, where 11/13 (85%) and 15/34 (44%) patients with at least one STK11/KEAP1/EGFR alteration showed durable treatment benefit in the discovery and validation cohorts, respectively. These findings were supported by analyses of progression-free survival and overall survival.

CONCLUSIONS

The unexpected ICB responses in patients carrying resistance biomarkers in STK11, KEAP1, and EGFR were almost exclusively observed in patients with a high TMB. Considering these alterations in context, the TMB offered a highly specific combinatorial biomarker strategy for limiting overtreatment in NSCLC.

Glutamine antagonist DRP-104 suppresses tumor growth and enhances response to checkpoint blockade in KEAP1 mutant lung cancer

Loss-of-function mutations in KEAP1 frequently occur in lung cancer and are associated with poor prognosis and resistance to standard of care treatment, highlighting the need for the development of targeted therapies. We previously showed that KEAP1 mutant tumors consume glutamine to support the metabolic rewiring associated with NRF2-dependent antioxidant production. Here, using preclinical patient-derived xenograft models and antigenic orthotopic lung cancer models, we show that the glutamine antagonist prodrug DRP-104 impairs the growth of KEAP1 mutant tumors. We find that DRP-104 suppresses KEAP1 mutant tumors by inhibiting glutamine-dependent nucleotide synthesis and promoting antitumor T cell responses. Using multimodal single-cell sequencing and ex vivo functional assays, we demonstrate that DRP-104 reverses T cell exhaustion, decreases Tregs, and enhances the function of CD4 and CD8 T cells, culminating in an improved response to anti-PD1 therapy. Our preclinical findings provide compelling evidence that DRP-104, currently in clinical trials, offers a promising therapeutic approach for treating patients with KEAP1 mutant lung cancer.

Development, testing and validation of a targeted NGS-panel for the detection of actionable mutations in lung cancer (NSCLC) using anchored multiplex PCR technology in a multicentric setting

Lung cancer is a paradigm for a genetically driven tumor. A variety of drugs were developed targeting specific biomarkers requiring testing for tumor genetic alterations in relevant biomarkers. Different next-generation sequencing technologies are available for library generation: 1) anchored multiplex-, 2) amplicon based- and 3) hybrid capture-based-PCR. Anchored multiplex PCR-based sequencing was investigated for routine molecular testing within the national Network Genomic Medicine Lung Cancer (nNGM). Four centers applied the anchored multiplex ArcherDX-Variantplex nNGMv2 panel to re-analyze samples pre-tested during routine diagnostics. Data analyses were performed by each center and compiled centrally according to study design. Pre-defined standards were utilized, and panel sensitivity was determined by dilution experiments. nNGMv2 panel sequencing was successful in 98.9% of the samples (N = 90). With default filter settings, all but two potential MET exon 14 skipping variants were identified at similar allele frequencies. Both MET variants were found with an adapted calling filter. Three additional variants (KEAP1, STK11, TP53) were called that were not identified in pre-testing analyses. Only total DNA amount but not a qPCR-based DNA quality score correlated with average coverage. Analysis was successful with a DNA input as low as 6.25 ng. Anchored multiplex PCR-based sequencing (nNGMv2) and a sophisticated user-friendly Archer-Analysis pipeline is a robust and specific technology to detect tumor genetic mutations for precision medicine of lung cancer patients.

Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact

BACKGROUND

Cancer, a disease with high morbidity and mortality rates, poses a significant threat to human health. Driver genes, which harbor mutations accountable for the initiation and progression of tumors, play a crucial role in cancer development. Identifying driver genes stands as a paramount objective in cancer research and precision medicine.

RESULTS

In the present work, we propose a method for identifying driver genes using a Generalized Linear Regression Model (GLM) with Shrinkage and double-Weighted strategies based on Functional Impact, which is named GSW-FI. Firstly, an estimating model is proposed for assessing the background functional impacts of genes based on GLM, utilizing gene features as predictors. Secondly, the shrinkage and double-weighted strategies as two revising approaches are integrated to ensure the rationality of the identified driver genes. Lastly, a statistical method of hypothesis testing is designed to identify driver genes by leveraging the estimated background function impacts. Experimental results conducted on 31 The Cancer Genome Altas datasets demonstrate that GSW-FI outperforms ten other prediction methods in terms of the overlap fraction with well-known databases and consensus predictions among different methods.

CONCLUSIONS

GSW-FI presents a novel approach that efficiently identifies driver genes with functional impact mutations using computational methods, thereby advancing the development of precision medicine for cancer.

Clinical outcome and molecular landscape of patients with ARID1A-loss gastric cancer

Chromatin remodelers are commonly altered in human cancer. The mutation of AT-rich interactive domain 1A (ARID1A) in gastric cancer (GC), a component of the SWI/SNF chromatin remodeling complex, was proven associated with treatment response in our previous study. However, ARID1A loss of function was caused not only by mutations but also copy number deletions. The clinicopathologic, genomic, and immunophenotypic correlates of ARID1A loss is largely uncharacterized in GC. Here, 819 patients with clinicopathological information and sequencing data or formalin-fixed paraffin-embedded tissues from four cohorts, Zhongshan Hospital (ZSHS) cohort (n = 375), The Cancer Genome Atlas (TCGA) cohort (n = 371), Samsung Medical Center (SMC) cohort (n = 53), and ZSHS immunotherapy cohort (n = 20), were enrolled. ARID1A loss was defined by genome sequencing or deficient ARID1A expression by immunohistochemistry. We found that ARID1A mutation and copy number deletion were enriched in GC with microsatellite instability (MSI) and chromosomal-instability (CIN), respectively. In the TCGA and ZSHS cohorts, only CIN GC with ARID1A loss could benefit from fluorouracil-based adjuvant chemotherapy. In the SMC and ZSHS immunotherapy cohorts, ARID1A loss exhibited a tendency of superior responsiveness and indicated favorable overall survival after anti-PD-1 immunotherapy. ARID1A-loss tumors demonstrated elevated mutation burden, neoantigen load, and interferon gamma pathway activation. Moreover, in CIN GC, ARID1A loss was correlated with higher homologous recombination deficiency. ARID1A loss defines a distinct subtype of GC characterized by high levels of genome instability, neoantigen formation, and immune activation. These tumors show sensitivity to both chemotherapy and anti-PD-1 immunotherapy. This study provides valuable insights for precision treatment strategies in GC.

Microsatellite Instability and Mismatch Repair Deficiency Define a Distinct Subset of Lung Cancers Characterized by Smoking Exposure, High Tumor Mutational Burden, and Recurrent Somatic MLH1 Inactivation

INTRODUCTION

Microsatellite instability (MSI) and mismatch repair (MMR) deficiency represent a distinct oncogenic process and predict response to immune checkpoint inhibitors (ICIs). The clinicopathologic features of MSI-high (MSI-H) and MMR deficiency (MMR-D) in lung cancers remain poorly characterized.

METHODS

MSI status from 5171 patients with NSCLC and 315 patients with SCLC was analyzed from targeted next-generation sequencing data using two validated bioinformatic pipelines.

RESULTS

MSI-H and MMR-D were identified in 21 patients with NSCLC (0.41%) and six patients with SCLC (1.9%). Notably, all patients with NSCLC had a positive smoking history, including 11 adenocarcinomas. Compared with microsatellite stable cases, MSI-H was associated with exceptionally high tumor mutational burden (37.4 versus 8.5 muts/Mb, p < 0.0001), MMR mutational signatures (43% versus 0%, p < 0.0001), and somatic biallelic alterations in MLH1 (52% versus 0%, p < 0.0001). Loss of MLH1 and PMS2 expression by immunohistochemistry was found in MLH1 altered and wild-type cases. Similarly, the majority of patients with MSI-H SCLC had evidence of MLH1 inactivation, including two with MLH1 promoter hypermethylation. A single patient with NSCLC with a somatic MSH2 mutation had Lynch syndrome as confirmed by the presence of a germline MSH2 mutation. Among patients with advanced MSI-H lung cancers treated with ICIs, durable clinical benefit was observed in three of eight patients with NSCLC and two of two patients with SCLC. In NSCLC, STK11, KEAP1, and JAK1 were mutated in nonresponders but wild type in responders.

CONCLUSIONS

We present a comprehensive clinicogenomic landscape of MSI-H lung cancers and reveal that MSI-H defines a rare subset of lung cancers associated with smoking, high tumor mutational burden, and MLH1 inactivation. Although durable clinical benefit to ICI was observed in some patients, the broad range of responses suggests that clinical activity may be modulated by co-mutational landscapes.

Single-cell and Bulk RNA-Seq reveal angiogenic heterogeneity and microenvironmental features to evaluate prognosis and therapeutic response in lung adenocarcinoma

Background

Angiogenesis stands as a pivotal hallmark in lung adenocarcinoma (LUAD), intricately shaping the tumor microenvironment (TME) and influencing LUAD progression. It emerges as a promising therapeutic target for LUAD, affecting patients' prognosis. However, its role in TME, LUAD prognosis, and its clinical applicability remain shrouded in mystery.

Methods

We employed integrated single-cell and bulk transcriptome sequencing to unravel the heterogeneity of angiogenesis within LUAD cells. Through "consensus clustering", we delineated distinct angiogenic clusters and deciphered their TME features. "Monocle2" was used to unravel divergent trajectories within malignant cell subpopulations of LUAD. Additionally, regulon submodules and specific cellular communication patterns of cells in different angiogenic states were analyzed by "pyscenic" and "Cellchat" algorithms. The "univariate Cox" and "LASSO" algorithms were applied to build angiogenic prognostic models. Immunohistochemistry (IHC) on clinical samples validated the role of model factors in LUAD angiogenesis. We utilized CTRP 2.0 and PRISM databases for pinpointing sensitive drugs against lung adenocarcinoma.

Results

Two clusters for the activation of angiogenesis were identified, with Cluster 1 showing a poor prognosis and a pro-cancerous TME. Three differentiated states of malignant epithelial LUAD cells were identified, which had different degrees of angiogenic activation, were regulated by three different regulon submodules, and had completely different crosstalk from other cells in TME. The experiments validate that SLC2A1 promotes angiogenesis in LUAD. ARS (Angiogenesis related score) had a high prognostic value; low ARSs showed immunotherapy benefits, whereas high ARSs were sensitive to 15 chemotherapeutic agents.

Conclusion

The assessment of angiogenic clusters helps to determine the prognostic and TME characteristics of LUAD. Angiogenic prognostic models can be used to assess the prognosis, immunotherapeutic response, and chemotherapeutic drug sensitivity of LUAD.

A novel transcriptomic signature associated with lymphovascular invasion predicts clinical outcomes, tumor microenvironment, and therapeutic response in lung adenocarcinoma

PURPOSE

Since TNM staging has limitations for predicting post-operative outcomes and relapse, more effective prediction tools need to be researched and developed. Lymphovascular invasion, LVI, as a histopathological feature, has been widely shown to have a correlation with poor prognosis and early recurrence of lung adenocarcinoma (LUAD). However, LVI assessment is limited by subjective bias, and therefore its efficacy in practical clinical application needs further clarification. The aim of this study was to formulate a new signature based on LVI-related genes to predict prognosis and recurrence in patients with lung adenocarcinoma.

METHODS

Clinicopathological information, gene sequencing data and whole slide images (WSIs) of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA) databases. LVI statue were evaluated by professional pathologists, and then the differentially expressed genes (LVI DEGs) associated with LVI were screened. The least absolute shrinkage and selection operator (LASSO) and Step Cox regression models were used to construct LVI-associated risk scores (LVRS), including PAQR4, ARGHEF6, CKS1B, CFTR and SEC14L4. The validity of the LVRS score was evaluated on multiple external datasets and our JSSZL cohort dataset. Using LVRS scores and clinical information, nomogram were constructed for use by clinicians. In addition, we further explored the relationship between LVRS score and clinicopathological features, immune infiltration, tumor mutational load, and immunotherapy response, and confirmed the expression of key genes in LVRS score in lung adenocarcinoma tissues using qRT-PCR and immunohistochemistry (IHC) techniques.

RESULTS

Based on the LVRS, patients could be classified into high-LVRS and low-LVRS groups. It was found that OS and PFS were significantly worse in the high-LVRS group than in the low-LVRS group (p < 0.001). By ROC curve analysis, it could be found that the nomogram combining LVRS and clinical information could accurately predict the prognosis of LUAD patients with the area under the curve of 1,3,5-year survival rate could reach 0.754, 0.741 and 0.735. The results of univariate and multivariate analysis showed that LVRS was an independent prognostic factor. At the same time, there were significant differences in the mutation profiles and immune microenvironment between the high-LVRS and low-LVRS groups, with the high-LVRS group having a significantly higher mutation rate than the low-LVRS group and exhibiting immunological "cold" features. By the experimental results, higher expression levels of PAQR4 and CKS1B were found in LUAD tissues, while lower expression levels of ARGHEF6, CFTR and SEC14L4 were observed.

CONCLUSIONS

The LVRS established in this study serves as a valid tool to predict the prognosis and recurrence status of lung adenocarcinoma patients and has a predictive effect on the response to postoperative treatment. The establishment of LVRS may offer some theoretical support to clinical treatment strategies for patients with lung adenocarcinoma following surgical intervention.

STK11/LKB1-Deficient Phenotype Rather Than Mutation Diminishes Immunotherapy Efficacy and Represents STING/Type I Interferon/CD8+ T-Cell Dysfunction in NSCLC

INTRODUCTION

Conflicting findings have been reported regarding the association between STK11/LKB1 mutations and immune checkpoint inhibitor (ICB) efficacy in NSCLC. It has been reported that tumors could exhibit impaired STK11/LKB1 function even without STK11 mutations. We hypothesized that STK11 phenotype rather than mutation may better stratify ICB outcomes.

METHODS

Selected functional STK11 events and LKB1 protein data were leveraged to establish a transcriptomics-based classifier of STK11 phenotype (STK11-deficient [-def] or -proficient [-prof]). We analyzed in-house and Genentech/Roche's data of three randomized trials of programmed cell death protein-1 or programmed death-ligand 1 (PD-L1) inhibition in NSCLC (ORIENT-11, n = 171; OAK, n = 699; POPLAR, n = 192) and The Cancer Genome Atlas-NSCLC cohort.

RESULTS

Tissue STK11 mutation did not affect ICB outcomes. However, the survival benefit of ICB versus chemotherapy were lost or reversed in STK11-def tumors (hazard ratios for death, 95% confidence interval: OAK [0.97, 0.69-1.35]; POPLAR [1.61, 0.88-2.97]; ORIENT-11 [1.07, 0.50-2.29]), while remaining in STK11-prof tumors (hazard ratios for death, 95% confidence interval: OAK [0.81, 0.66-0.99]; POPLAR [0.66, 0.46-0.95]; ORIENT-11 [0.59, 0.37-0.92]). In tumors differentially classified by phenotype and mutation status, STK11-wild-type/def tumors had significantly worse ICB outcomes than STK11-mutated (STK11-MUT)/prof tumors (p < 0.05). The deleterious impact of STK11 deficiency was independent of STK11/KRAS/KEAP1 status or PD-L1 expression. The STING/interferon-I signaling, which was previously shown to be suppressed in STK11-MUT models, was perturbed in patients with STK11-def tumors rather than those with STK11-MUT tumors. Surprisingly, whereas high CD8+ T-cell infiltration was significantly associated with prolonged survival with ICB in STK11-prof tumors (p < 0.05 for 3 trials), it predicted an opposite trend toward worse ICB outcomes in STK11-def tumors across three trials. This suggested an association between STK11 deficiency and CD8+ T-cell dysfunction, which might not be reversed by programmed cell death protein 1 or PD-L1 blockade.

CONCLUSIONS

STK11 phenotype rather than mutation status can accurately identify patients with ICB-refractory NSCLC and reflect immune suppression. It can help refine stratification algorithms for future clinical research and also provide a reliable resource aiding basic and translational studies in identifying therapeutic targets.

KEAP1 mutation in lung adenocarcinoma promotes immune evasion and immunotherapy resistance

Lung cancer treatment has benefited greatly through advancements in immunotherapies. However, immunotherapy often fails in patients with specific mutations like KEAP1, which are frequently found in lung adenocarcinoma. We established an antigenic lung cancer model and used it to explore how Keap1 mutations remodel the tumor immune microenvironment. Using single-cell technology and depletion studies, we demonstrate that Keap1-mutant tumors diminish dendritic cell and T cell responses driving immunotherapy resistance. This observation was corroborated in patient samples. CRISPR-Cas9-mediated gene targeting revealed that hyperactivation of the NRF2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant tumors. Importantly, we demonstrate that combining glutaminase inhibition with immune checkpoint blockade can reverse immunosuppression, making Keap1-mutant tumors susceptible to immunotherapy. Our study provides new insight into the role of KEAP1 mutations in immune evasion, paving the way for novel immune-based therapeutic strategies for KEAP1-mutant cancers.

Whole brain radiation therapy resulting in radionecrosis: a possible link with radiosensitising chemoimmunotherapy

Radionecrosis describes a rare but serious complication of radiation therapy. In clinical practice, stereotactic radiosurgery (SRS) is increasingly used in combination with systemic therapy, including chemotherapy, immune checkpoint inhibitor and targeted therapy, either concurrently or sequentially. There is a paucity of literature regarding radionecrosis in patients receiving whole brain radiation therapy (WBRT) alone (without additional SRS) in combination with immunotherapy or targeted therapies. It is observed that certain combinations increase the overall radiosensitivity of the tumorous lesions. We present a rare case of symptomatic radionecrosis almost 1 year after WBRT in a patient with non-squamous non-small cell lung cancer on third-line chemoimmunotherapy. We discuss available research regarding factors that may lead to radionecrosis in these patients, including molecular and genetic profiles, specific drug therapy combinations and their timing or increased overall survival.

Fusing WGCNA and Machine Learning for Immune-Related Gene Prognostic Index in Lung Adenocarcinoma: Precision Prognosis, Tumor Microenvironment Profiling, and Biomarker Discovery

Background

The objective is to create an IRGPI (Immune-related genes prognostic index), which could predict the survival and effectiveness of immune checkpoint inhibitor (ICI) treatment for lung adenocarcinoma (LUAD).

Methods

By applying weighted gene co-expression network analysis (WGCNA), we ascertained 13 genes associated with immune functions. An IRGPI was constructed using four genes through multicox regression, and its validity was assessed in the GEO dataset. Next, we explored the immunological and molecular attributes and advantages of ICI treatment in subcategories delineated by IRGPI. The model genes were also validated by the random forest tree, and functional experiments were conducted to validate it.

Results

The IRGPI relied on the genes CD79A, IL11, CTLA-4, and CD27. Individuals categorized as low-risk exhibited significantly improved overall survival in comparison to those classified as high-risk. Extensive findings indicated that the low-risk category exhibited associations with immune pathways, significant infiltration of CD8 T cells, M1 macrophages, and CD4 T cells, a reduced rate of gene mutations, and improved sensitivity to ICI therapy. Conversely, the higher-risk group displayed metabolic signals, elevated frequencies of TP53, KRAS, and KEAP1 mutations, escalated levels of NK cells, M0, and M2 macrophage infiltration, and a diminished response to ICI therapy. Additionally, our study unveiled that the downregulation of IL11 effectively impedes the proliferation and migration of lung carcinoma cells, while also inducing cell cycle arrest.

Conclusion

IRGPI is a biomarker with significant potential for predicting the effectiveness of ICI treatment in LUAD patients and is closely related to the microenvironment and clinicopathological characteristics.

Classification of SLC family-related genes involved in ferroptosis predicts lung cancer prognosis and immunotherapy response

Lung adenocarcinoma, the most frequent type of lung cancer, is the leading cause of cancer-related deaths worldwide. Ferroptosis, controlled cell death that involves a high degree of iron-dependent lipid peroxidation, has been linked to tumor therapy sensitivity, patient prognosis, and cancer development. The solute carrier superfamily has over 400 members and comprises the largest class of transporters in the human genome. Solute carrier proteins can facilitate the movement of different substrates across biological membranes, which is crucial for physiological activities, including ferroptosis. Here, we developed a new model to further explore the role of the solute carrier family in ferroptosis in the lung adenocarcinoma immunological milieu. We used consensus clustering to classify patients with lung cancer into two subgroups (cluster1 and cluster2). Patients in the cluster1 subtype had a better prognosis and higher immune cell infiltration ratios than those in the cluster2 subtype. Furthermore, to evaluate the prognosis, the immune cell infiltration ratio, and the medication sensitivity of patients with lung adenocarcinoma, we developed gene scores related to the solute carrier family. In conclusion, we successfully developed a model incorporating the solute carrier family and ferroptosis to predict survival and the impact of immunotherapy on patients with lung cancer.

KEAP1/NFE2L2 Pathway Signature Outperforms KEAP1/NFE2L2 Mutation Status and Reveals Alternative Pathway-Activating Mutations in NSCLC

INTRODUCTION

Activation of the antioxidant KEAP1/NFE2L2 (NRF2) pathway leads to increased glutamine dependence and an aggressive phenotype in NSCLC. Because this pathway has been explored as a clinical target, we developed a transcriptomic signature for identifying KEAP1/NFE2L2-activated tumors.

METHODS

A total of 971 NSCLC samples were used to train an expression signature (K1N2-score) to predict KEAP1/NFE2L2 mutations. There were 348 in-house NSCLCs that were analyzed using a NanoString expression panel for validation.

RESULTS

The 46-gene K1N2 score robustly predicted KEAP1/NFE2L2 mutations in the validation set irrespective of histology and mutation (area under the curve: 89.5, sensitivity: 90.2%), suggesting that approximately 90% of KEAP1/NFE2L2 mutations are pathway-activating. The K1N2-score outperformed KEAP1/NFE2L2 mutational status when predicting patient survival (score p = 0.047; mutation p = 0.215). In K1N2 score-positive but KEAP1/NFE2L2 wild-type samples, enrichment testing identified SMARCA4/BRG1 and CUL3 mutations as mimics of KEAP1/NFE2L2 mutations.

CONCLUSIONS

The K1N2-score identified KEAP1/NFE2L2-activated NSCLC by robustly detecting KEAP1/NFE2L2mut cases and discovering alternative genomic activators. It is a potential means for selecting patients with a constitutively active KEAP1/NFE2L2 pathway.