Genomic landscape of lung adenocarcinoma in East Asians

Cell Death and Senescence-Based Molecular Classification and an Individualized Prediction Model for Lung Adenocarcinoma

The exploration of cell death and cellular senescence (CDS) in cancer has been an area of interest, yet a systematic evaluation of CDS features and their interactions in lung adenocarcinoma (LUAD) to understand tumor heterogeneity, tumor microenvironment (TME) characteristics, and patient clinical outcomes is previously uncharted. Our study characterized the activities and interconnections of 21 CDS features in 1788 LUAD cases across 15 cohorts, employing unsupervised clustering to categorize patients into three CDS subtypes with distinct TME profiles. The CDS index (CDSI), derived from principal component analysis, was developed to assess individual tumor CDS regulation patterns. Twelve CDSI core genes, enriched in proliferating T cells within the TME as per single-cell analysis, were identified and their functional roles and prognostic significance were validated. High CDSI correlated with improved overall survival in discovery cohort, four independent validation cohorts, and subgroup analysis. CDSI-low patients exhibited a favorable clinical response to immunotherapy and potential sensitivity to mitosis pathway drugs, while CDSI-high patients might benefit from drugs targeting ERK/MAPK and MDM2-p53 pathways. The clinical utility of CDSI was further validated using 9185 pan-cancer samples, demonstrating the broad relevance of our prediction model across various cancer types and its potential clinical implications for cancer management.

Multi-omics analyses reveal distinct molecular characteristics and transformation mechanisms of stage I-III micropapillary lung adenocarcinoma

The micropapillary (MIP) pattern is a high-grade histological subtype of lung adenocarcinoma (LUAD) with poor prognosis. In this study, surgically resected tumor samples from 101 patients with stage I-III MIP-LUAD (MIP ≥30%) were microdissected to separate MIP components from non-MIP components, all of which underwent RNA and DNA whole-exome sequencing (WES). The genomic and transcriptomic landscapes of MIP and non-MIP components within MIP-enriched tumor tissues demonstrated remarkable similarities, notably marked by high epidermal growth factor receptor (EGFR) alteration frequencies. However, when compared to MIP-naïve LUAD tissues, MIP components showed higher chromosomal instability and revealed 18 enriched alterations, encompassing EGFR mutations, EGFR amplifications, and CDKN2A/CDKN2B deletions, which all linked to upregulation of cell proliferation pathways and downregulation of immune pathways. Shared mutations were observed in 97.8% (91/93) of patients with paired DNA WES data for MIP and non-MIP components within the same tissues, suggesting a common origin. The recurrence-free survival analysis identified MACF1, PCLO, ADGRV1, and Fanconi Anemia pathway mutations as negative indicators. In all, we conducted an in-depth analysis of the molecular characteristics and transformation mechanisms of MIP-LUAD, employing microdissection techniques to investigate the genomic and transcriptomic levels within a substantial cohort, providing insights for precision medicine of this aggressive cancer subtype. © 2025 The Pathological Society of Great Britain and Ireland.

A Pilot Study: Contrasting Genomic Profiles of Lung Adenocarcinoma Between Patients of European and Latin American Ancestry

Lung cancer remains as the leading cause of cancer mortality worldwide. However, while current evidence suggests the existence of genomic differences between populations, indicating different risk factors associated with population-level genetic backgrounds, most studies have concentrated on populations of European ancestry, and more research is needed on non-European populations. We analyzed whole-exome sequencing data from 25 Mexican lung adenocarcinoma patients and compared them with a TCGA-PanCancer cohort enriched with patients of European ancestry as reference. Clinically relevant germline variants in cancer susceptibility genes are more frequent in our cohort (32% vs. 6.4%) than in the reference. Several mutational signatures (SBS32, SBS85, SBS12, SBS19) occurred at significantly higher frequencies in the Mexican cohort compared to the reference (p < 0.0001). Interestingly, the smoking-associated signature SBS4, present in 67.6% of smokers in the reference cohort, was absent in smoking Mexican patients (p < 0.01656). Somatic variant frequencies in SLC36A4 (20%; p < 0.00002), AP1S1 (8%; p < 0.00002), and TP53 (16%; p = 0.00005) showed significant differences from the European reference cohort. We demonstrate that all these observed biases were independent of the sample size. This study uncovers distinct genomic biases in lung cancer carcinogenesis in this population, compared to a European ancestry reference population, suggesting implications for precision medicine strategies in Latin American populations.

Nebulized inhalation of extracellular vesicles containing SPOCK2 suppresses lung adenocarcinoma progression via MAPK inhibition

Aberrant expression of SPARC/osteonectin, cwcv and kazal-like domains proteoglycan 2 (SPOCK2) plays a role in the development and progression of several human cancers. However, the importance of its expression and function in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to elucidate the role of SPOCK2 in the growth of LUAD and propose a novel therapeutic insight for LUAD through SPOCK2. SPOCK2 protein expression was significantly reduced in LUAD tissues and cells by Immunohistochemical assay and Western blot. CCK-8, colony formation, and Transwell assays were used to demonstrate that SPOCK2 overexpression inhibited both proliferation and migration of LUAD cells in vitro. This inhibition of tumor growth was further confirmed by a LUAD xenograft mouse model in vivo. To explore downstream target signal of SPOCK2 in LUAD, RNA transcriptome sequencing was performed and enrichment analysis showed an association between SPOCK2 expression and the MAPK pathway. Furthermore, HEK293T cells were modified with SPOCK2, and extracellular vesicles (EVs) containing SPOCK2 (SPOCK2-EVs) were collected through ultra-high-speed centrifugation. Interestingly, co-culture with SPOCK2-EVs significantly increased SPOCK2 levels within LUAD cells. Furthermore, SPOCK2-EVs effectively inhibited LUAD growth in vitro and in vivo studies. Because directly injecting SPOCK2-EVs into tumors presents challenges for internal organs, we investigated the efficacy of nebulized SPOCK2-EVs for LUAD treatment. Consistent with our findings from intratumoral injection, nebulized inhalation of SPOCK2-EVs resulted in significant inhibition of LUAD growth. These results strongly suggest that SPOCK2 released by HEK293T-EVs can effectively inhibit LUAD tumor growth and hold promise for future clinical translation in cancer therapy.

Potential Crosstalk Between ANXA1+ Epithelial Cells and FABP4+ TAM Cells of Ferroptosis-Related Molecular Clusters Promotes an Immunosuppressive Microenvironment in Non-Small Cell Lung Cancer

The tumor microenvironment (TME) affects tumor initiation, invasion, metastasis, and therapies. Recently, increasing evidence has demonstrated that ferroptosis plays important regulatory roles in tumourigenesis and progression. It is unclear how ferroptosis affects non-small cell lung cancer (NSCLC) progression by remodeling the TME. In this study, the single-cell RNA sequencing (scRNA-seq) data (85,562 cells, n = 18) were employed to reveal the heterogeneity of ferroptosis activation in NSCLC, and identified six ferroptosis-related molecular clusters. We found that ANXA1+ epithelial and FABP4 + TAM subpopulations were key factors in lung cancer progression and TME remodeling. In addition, the cell-cell communication analysis showed that ANXA1-FPR2/FPR1 receptor-ligand pair contributed to the formation of an immunosuppressive TME. Furthermore, we established a novel signature based on ferroptosis-related molecular clusters, and the risk score model may predict survival and response to immunotherapy. We also found that compared with responder, the expression of ANXA1 and FABP4 is higher in progressor, which indicating a higher expression of ANXA1 and FABP4 was associated with a worse response to immunotherapy. Therefore, we concluded that the molecular clusters associated with ferroptosis served as potential prognostic markers and therapeutic targets for NSCLC patients.

Unveiling hypoxia-related prognostic and immunotherapeutic biomarkers in lung adenocarcinoma through single-cell and bulk RNA sequencing: Including insights into PGF

Hypoxia plays a crucial role in lung adenocarcinoma (LUAD) proliferation and metastasis. However, the mechanisms underlying the interaction between the hypoxic microenvironment and immune resistance remain unclear. In this study, single-cell RNA sequencing (scRNA-seq) data from 15 LUAD patients were used to evaluate the complexity and heterogeneity of tumor microenvironment (TME). We identified new subtypes associated with advanced LUAD, including epithelial cells, fibroblasts, and myeloid cells. Furthermore, we found that the cell subtype module 3 (AGER, TIMP3) of epithelial cells exhibited higher hypoxia scores in advanced LUAD. Meanwhile, we also observed that RSG5 + fibroblast, AOPE+macrophage, S100B + macrophage, CCL17 + macrophage, and HLA-DRB5 + macrophage cells exhibited higher hypoxia scores in advanced LUAD patients. Moreover, spatial transcriptomic analysis revealed that with the gradual decrease of hypoxia score, the cell type score also gradually decreased. Cell communication analysis identified critical receptor-ligand pairs, which were associated with the activation of the PD-1/PD-L1 pathway. Finally, we developed a novel prognostic signature based on hypoxia-related molecular clusters, which possessed predictive power for both prognosis and immunotherapy response. The experimental results confirmed that hypoxia-related genes play a significant role in driving LUAD progression. In conclusion, our study provides valuable insights into the hypoxic and immunosuppressive tumor microenvironment, which serve as a potential prognostic marker and therapeutic target for LUAD.

Genomic profiling of aggressive pathologic features in lung adenocarcinoma

INTRODUCTION

Pathologic features involving LVI (lympho-vascular invasion), PNI (perineural invasion), STAS (spread through air spaces), and Grade 3 pattern (from the International Association for the Study of Lung Cancer grading system) are related to having an aggressive phenotype and linked to poor prognosis. However, few studies have conducted in-depth analyses of these features simultaneously with genomic profiling.

METHODS

A total of 1559 sequencing of adenocarcinoma samples were included in the common driver mutations analysis, 1306 samples were brought into genomic mapping analysis. OncoSG's East Asian ancestry dataset was implemented for Tumor-Node-Metastasis-Biomarker (TNMB) classification and prognostic assessment.

RESULTS

EGFR was more significantly prevalent in LVI negativity (P = 0.021), STAS negativity (P = 0.002), and moderate grade (P < 0.001). ALK was significantly interrelated with LVI (P = 0.028), STAS (P < 0.001), and poor grade (P < 0.001); ROS1 and STAS positivity (P = 0.031), poor grade (P = 0.016) were significantly related. KRAS (P = 0.003) and BRAF-V600E (P = 0.002) were only significantly intertwined with poor grade. Apart from common driver mutations, TP53, CHEK2, KEAP1, PTEN, RB1, NF1 were significantly enriched in LVI samples (P < 0.05). TP53, PTEN, CTNNB1, HGF, NF1 were more prominent in STAS (P < 0.01). TP53, LRP1B, NF1 were significantly more prevalent in Grade 3 pattern (P < 0.001). The mixture of STK11, PTEN, and TOP2A generated by exclusive mutations may be a potential predictor of TNMB categorization towards survival. The HR of stage II compared I of TNMB was 2.28 (95 % CI 1.36-3.86, P < 0.001), while stage III compared II was 1.95 (95 % CI 1.04-3.21, P = 0.031).

CONCLUSIONS

This analysis demonstrated the correlation of pathologic features with common driver mutations, key mutations and canonical oncogenic signaling pathways. The data highlighted the similarities and differences among these features horizontally, and provide new insights in TNMB classification and prognostic assessment.

Multi‑omics analysis identifies different molecular subtypes with unique outcomes in early-stage poorly differentiated lung adenocarcinoma

INTRODUCTION

Early-stage poorly differentiated lung adenocarcinoma (LUAD) is plagued by a high risk of postoperative recurrence, and its prognostic heterogeneity complicates treatment and surveillance planning. We conducted this integrative multi-omics study to identify those patients with a truly high risk of adverse outcomes.

METHODS

Whole-exome, RNA and whole methylome sequencing were carried out on 101 treatment-naïve early-stage poorly differentiated LUADs. Integrated analyses were conducted to disclose molecular characteristics and explore molecular subtyping. Functional validation of key molecules was carried out through in vitro and in vivo experiments.

RESULTS

Recurrent tumors exhibited significantly higher ploidy (p = 0.024), the fraction of the genome altered (FGA, p = 0.042), and aneuploidy (p < 0.05) compared to non-recurrent tumors, as well as a higher frequency of CNVs. Additionally, recurrent tumors showed hypomethylation at both the global level and in CpG island regions. Integrative transcriptomic and methylation analyses identified three molecular subtypes (C1, C2, and C3), with the C1 subtype presenting the worst prognosis (p = 0.024). Although frequently mutated genes showed similar mutation frequencies across the three subtypes, the C1 subtype exhibited the highest tumor mutation burden (TMB), mutant-allele tumor heterogeneity (MATH), aneuploidy, and HLA loss of heterozygosity (HLA-LOH), along with relatively lower immune cell infiltration. Furthermore, GINS1 and CPT1C were found to promote LUAD progression, and their high expression correlated with a poor prognosis.

CONCLUSIONS

This multi-omics study identified three integrative subtypes with distinct prognostic implications, paving the way for more precise management and postoperative monitoring of early-stage poorly differentiated LUAD.

Cost-Utility Analysis of Genomic Profiling in Directing Targeted Therapy in Advanced NSCLC in Thailand

BACKGROUND

Sequential next-generation sequencing (NGS) testing has demonstrated cost-effectiveness in guiding targeted therapy with tyrosine kinase inhibitors (TKIs) for advanced non-small cell lung cancer (aNSCLC) in developed countries. However, its cost-effectiveness in developing countries remains uncertain.

OBJECTIVE

The aim was to conduct a cost-utility analysis comparing sequential NGS testing with the current approach of single epidermal growth factor receptor (EGFR) testing combined with first-line targeted therapy, as implemented under Thailand's Universal Health Coverage scheme for aNSCLC.

METHOD

Hybrid decision tree and Markov models were developed to estimate the lifetime costs and quality-adjusted life years (QALYs) associated with each strategy. The models simulate cohorts of aNSCLC patients who receive platinum-based chemotherapy or TKIs based on identified gene alterations. Patients enter the model at 60 years of age. The incremental cost-effectiveness ratio (ICER) was computed from a societal perspective. The analysis employed a lifetime horizon and discounted costs and outcomes at a rate of 3%. Furthermore, uncertainty and scenario analyses were conducted.

FINDINGS

A sequential NGS testing strategy could identify an additional 19% of patients with biomarker-positive findings who subsequently received biomarker-driven targeted therapy compared to a single EGFR testing strategy. The number needed to screen to identify a single gene mutation and administer first-line TKI was six for the sequential NGS testing strategy. Compared to the single EGFR testing, the ICER of the sequential NGS testing strategy was 1,851,150 THB/QALY (US$51,335). At a willingness-to-pay threshold of 160,000 THB/QALY (US$4437), the single EGFR testing strategy demonstrated 100% cost-effectiveness. In contrast, the sequential NGS testing was not deemed cost-effective. The sensitivity of the ICER was influenced by the overall survival rates associated with anaplastic lymphoma kinase (ALK) inhibitors and platinum-based chemotherapy.

INTERPRETATION

Sequential NGS testing identified a greater number of patients with aNSCLC eligible for targeted therapies, resulting in improved survival rates and enhanced QALYs compared to single EGFR testing. However, in the context of Thailand, sequential NGS testing was not cost-effective. The single EGFR testing strategy emerged as the most cost-effective option for guiding first-line targeted therapy.

Tumor microenvironment-driven resistance to immunotherapy in non-small cell lung cancer: strategies for Cold-to-Hot tumor transformation

Non-small cell lung cancer (NSCLC) represents a formidable challenge in oncology due to its molecular heterogeneity and the dynamic suppressive nature of its tumor microenvironment (TME). Despite the transformative impact of immune checkpoint inhibitors (ICIs) on cancer therapy, the majority of NSCLC patients experience resistance, necessitating novel approaches to overcome immune evasion. This review highlights shared and subtype-specific mechanisms of immune resistance within the TME, including metabolic reprogramming, immune cell dysfunction, and physical barriers. Beyond well-characterized components such as regulatory T cells, tumor-associated macrophages, and myeloid-derived suppressor cells, emerging players - neutrophil extracellular traps, tertiary lymphoid structures, and exosomal signaling networks - underscore the TME's complexity and adaptability. A multi-dimensional framework is proposed to transform cold, immune-excluded tumors into hot, immune-reactive ones. Key strategies include enhancing immune infiltration, modulating immunosuppressive networks, and activating dormant immune pathways. Cutting-edge technologies, such as single-cell sequencing, spatial transcriptomics, and nanomedicine, are identified as pivotal tools for decoding TME heterogeneity and personalizing therapeutic interventions. By bridging mechanistic insights with translational innovations, this review advocates for integrative approaches that combine ICIs with metabolic modulators, vascular normalizers, and emerging therapies such as STING agonists and tumor vaccines. The synergistic potential of these strategies is poised to overcome resistance and achieve durable antitumor immunity. Ultimately, this vision underscores the importance of interdisciplinary collaboration and real-time TME profiling in refining precision oncology for NSCLC, offering a blueprint for extending these advances to other malignancies.

FAM207A acts as a novel and potential biomarker in lung adenocarcinoma and shapes the immunesuppressive tumor microenvironment

The expression of Family with sequence similarity 207 member A( FAM207A) is closely related to the development, growth, and progression of various cancers. However, extensive research into its biological functions remains unexplored. In this study, we conducted a comprehensive biological information analysis of the Lung adenocarcinoma (LUAD) dataset to elucidate the foundational mechanisms underlying FAM207A's role in tumor development. The expression and clinical information of LUAD patients for FAM207A were extracted from the Cancer Genome Atlas (TCGA). Using Western blot, we assessed the expression levels of relevant proteins in LUAD cells and human lung epithelial cells. Subsequently, we employed Cox regression analysis to evaluate the prognostic significance of FAM207A in LUAD, along with gene set enrichment analysis (GSEA) to explore its potential biological functions and interactions with FAM207A's immune microenvironment. Finally, in vitro experiments confirmed that FAM207A significantly influences the proliferation and migration of LUAD cells. The results indicate that FAM207A mRNA and protein expression levels in LUAD tissues and cell are significantly elevated. Additionally, FAM207A high expression is significantly associated with a shorter overall survival (OS) and more advanced pathological stages. Furthermore, FAM207A expression is significantly linked to the expression of immunogenic markers in the LUAD tumor microenvironment. Gene set and KEGG enrichment analyses revealed that FAM207A is primarily associated with genes involved in adhesion and immune signaling pathways. Additionally, in vitro experiments demonstrated that FAM207A can effectively promote the proliferation and migration of LUAD cells. Our findings revealed that FAM207A is overexpressed in LUAD and is linked to a poor prognosis. Our study demonstrates the potential of FAM207A as an immunotherapeutic and predictive biomarker in LUAD.

Molecular characterization of early-stage lung adenocarcinoma presenting as subsolid nodules in a real-life European cohort

OBJECTIVES

Subsolid nodules emerged as frequent radiological variants of lung adenocarcinoma. Radiological features including solid-component prevalence and larger tumour dimensions prompt tumoral invasiveness guiding prognosis and management. Thus, we aimed to clarify the molecular grounds that dictate these radiological appearances and clinical behaviour in a real-life European-cohort. Additionally, following the growing interest toward targeted-therapies in early-stage diseases, we aimed to present real-life epidemiological data of actionable mutations in these patients.

METHODS

In this retrospective single-centre study, targeted next-generation sequencing was performed continuatively in all the resected subsolid lung adenocarcinomas in the period between May 2016 and December 2023. Clinico-radiological data were collected. The genetic landscape of our real-life European subsolid adenocarcinoma population is defined. Common and actionable mutations (frequency > 5%) relation to key clinico-radiological features are evaluated.

RESULTS

Overall, 156 subsolid adenocarcinomas were analysed. KRAS-mutations, mostly KRAS p.G12C, were the most prevalent followed by EGFR, including 25% uncommon EGFR-mutations, TP53 and MET mutations. Amongst the clinico-radiological variables, KRAS-mutations and KRAS p.G12C-mutation were associated to smoking history (≥ 20 pack/years), aggressive histologic subtype and higher consolidation-to-tumor ratio (CTR). Moreover, KRAS-mutated nodules had faster tumour-doubling-time. Conversely, EGFR-mutations were associated to female sex and lower CTR. The latter not being confirmed in common EGFR-mutations. Additionally, in common EGFR-mutated nodules, aggressive histological components were rarer.

CONCLUSION

Our study presents the molecular profile of subsolid lung adenocarcinoma in a real-life European-cohort. KRAS-mutations were the most prevalent, and were related to smoking history, higher CTR and faster growth. Conversely, common EGFR-mutations were rarer than expected and unrelated to smoking history and radiological features.

The diagnostic value of comprehensive next-generation sequencing for genetic mutations in suspected lung cancer cases with negative pathological cytology

INTRODUCTION

In recent clinical practice, driver gene mutations have been tested using multiplex PCR or next-generation sequencing (NGS), which help determine treatment strategies for non-small cell lung cancer (NSCLC). We developed a new analysis system, the Mutation Investigator using Next-era Sequencer (MINtS), using NGS, which allows for the detection of gene mutations even in cytology specimens with low tumor cell content. Due to its high sensitivity, MINtS has the potential to detect gene mutations even in specimens that are pathologically negative for cancer. In the present study, we examined the utility of MINtS-based mutation detection in cytology-negative specimens.

METHODS

We retrospectively analyzed the data of patients who were enrolled in the NEJ021A study, which was a prospective observational study investigating the performance of MINtS. Although NEJ021A was a multicenter study, we included only patients enrolled at Niigata University Medical and Dental Hospital.

RESULTS

Cytology specimens from 486 patients with suspected lung cancer were analyzed using MINtS. Among the cytology-positive cases, driver gene mutations were detected in 37.3 % (93/249) of patients, whereas in cytology-negative cases, driver gene mutations were detected in 20.2 % (47/233) of patients using MINtS. Of the 47 patients whose specimens were cytology-negative and MINtS-positive, 42 were histologically or clinically diagnosed with NSCLC and received treatment.

CONCLUSIONS

Even in patients without a pathological diagnosis of lung cancer, MINtS can identify driver gene mutations, which can be useful for guiding subsequent treatment decisions.

Transcriptional regulation by LKB1 in lung adenocarcinomas: Exploring oxidative stress, neuroglial and amino acid signatures

Lung adenocarcinoma (LUAD) is one of the most prevalent cancer types worldwide and has one of the poorest survival rates. Understanding its developpment is crucial for improving diagnosis, prognosis, and treatment. A key factor in LUAD is the frequent loss-of-function mutations in LKB1/STK11, a kinase that regulates metabolism. These mutations are linked to increased metastasis and worse clinical outcomes. In this study, we analyzed gene expression data from LUAD patients to explore how LKB1 mutations affect cancer behavior. We found that LKB1 mutations in KRAS-driven LUAD lead to widespread gene downregulation. By integrating avalaible protein interaction data, mass spectrometry analysis of LKB1 nuclear partners, and co-immunoprecipitations experiments, we identified BRG1, a chromatin activator and subunit of the BAF complex, as a nuclear partner of LKB1. Further analysis suggested that LKB1 mutations may impair BRG1 activity, disrupting chromatin regulation and gene expression. Notably, LUAD patients with mutated LKB1 showed gene expression patterns indicative of oxidative stress, defective neuronal-glial and neuroinflammation programs, and altered amino acid homeostasis. These changes resemble the roles LKB1 plays in neural crest stem cells, suggesting that LKB1 may reduce tumor aggressiveness in LUAD by maintaining a developmental gene expression program.

Decoding the Clinical and Molecular Signatures of EGFR Common, Compound, and Uncommon Mutations in NSCLC: A Brief Report

INTRODUCTION

EGFR mutations are key oncogenic drivers in lung adenocarcinoma (LUAD), predominantly affecting Asian, nonsmoking, and female populations. Although common mutations, such as exon 19 deletions and L858R, respond well to tyrosine kinase inhibitors (TKIs), uncommon EGFR mutations and compound variants exhibit variable treatment responses. This study aims to compare clinical characteristics and molecular profiles of patients with common, uncommon, and compound EGFR mutations, assessing their implications for therapy outcomes.

METHODS

We analyzed a multi-cohort genomic dataset of 19,163 patients with LUAD (5,212 with EGFR mutations), categorizing mutations into common, uncommon, and compound classes. Patient demographics, mutational signatures, and tumor microenvironment factors were assessed, with particular attention to smoking status and concomitant alterations in KRAS and TP53. Treatment outcomes were analyzed by time under treatment as a surrogate measure of TKI efficacy.

RESULTS

Uncommon EGFR mutations, comprising 8.9% of EGFR-altered cases, were significantly more frequent among smokers and associated with tobacco-related mutational signatures. Compared with common EGFR-mutant cases, tumors harboring uncommon EGFR mutations reported higher rates of EGFR amplifications, KRAS, and TP53 mutations. Uncommon mutations also exhibited higher tumor mutational burden and distinct transcriptional profiles linked to cell cycle activity. Median time on treatment with TKIs was notably shorter in patients with uncommon mutations (4.1 mo) than those with common and compound mutations (10.9 mo and 12.4 mo, respectively).

CONCLUSIONS

This study underscores the clinical and molecular heterogeneity of EGFR mutation classes in LUAD, highlighting the unique profile of uncommon mutations, particularly their association with smoking and co-mutations in KRAS and TP53. Comprehensive molecular testing, including next-generation sequencing, is crucial to identify these uncommon mutations and inform therapeutic decisions. Further investigation into the role of immunotherapy in patients with uncommon EGFR mutations is warranted given the tobacco-related molecular signatures and high tumor mutational burden associated with this subgroup.

Deep Clustering-Based Metabolic Stratification of Non-Small Cell Lung Cancer Patients Through Integration of Somatic Mutation Profile and Network Propagation Algorithm

As a common malignancy of the lower respiratory tract, non-small cell lung cancer (NSCLC) represents a major oncological challenge globally, characterized by high incidence and mortality rates. Recent research highlights the critical involvement of somatic mutations in the onset and development of NSCLC. Stratification of NSCLC patients based on somatic mutation data could facilitate the identification of patients likely to respond to personalized therapeutic strategies. However, stratification of NSCLC patients using somatic mutation data is challenging due to the sparseness of this data. In this study, based on sparse somatic mutation data from 4581 NSCLC patients from the Memorial Sloan Kettering Cancer Center (MSKCC) database, we systematically evaluate the metabolic pathway activity in NSCLC patients through the application of network propagation algorithm and computational biology algorithms. Based on these metabolic pathways associated with prognosis, as recognized through univariate Cox regression analysis, NSCLC patients are stratified using the deep clustering algorithm to explore the optimal classification strategy, thereby establishing biologically meaningful metabolic subtypes of NSCLC patients. The precise NSCLC metabolic subtypes obtained from the network propagation algorithm and deep clustering algorithm are systematically evaluated and validated for survival benefits of immunotherapy. Our research marks progress towards developing a universal approach for classifying NSCLC patients based solely on somatic mutation profiles, employing deep clustering algorithm. The implementation of our research will help to deepen the analysis of NSCLC patients' metabolic subtypes from the perspective of tumor microenvironment, providing a strong basis for the formulation of more precise personalized treatment plans.

Multi-gene panel sequencing reveals the relationship between driver gene mutation and clinical characteristics in lung adenocarcinoma

BACKGROUND

Testing of multiple cancer related genes using next-generation sequencing (NGS) has been widely used for personalized precision medicine of cancer. Integrated analysis of those NGS data and clinical data has offered new opportunities for investigating the relationship between driver genes' mutations and clinical characteristics in large cohorts. This study aims to explore the mutational landscape and its association with clinical features in a lung adenocarcinoma (LUAD) cohort.

METHODS

Tumor tissues from 132 LUAD patients were subjected to customized 30 genes targeted next-generation sequencing. Somatic mutations of the 30 genes were identified and annotated. Statistical analysis was performed to determine the cooccurrence of mutations of different driver genes and the association relationships between gene mutation and clinical features including gender and age.

RESULTS

A total of 96.97% (128/132) of LUAD patients experienced genetic mutations. EGFR had the highest mutation rate (81, 61.36%) among the 30 genes, followed by TP53 (80, 60.61%), BRAF (30, 22.73%), KRAS (21, 15.91%) and ROS1 (21, 15.91%). The L858R substitution and exon19 deletion were the predominant mutations of EGFR, accounting for 82.71% of EGFR-mutated patients. The 27 mutation sites of EGFR were mainly located in the tyrosine kinase catalytic domain (22/27, 81.48%). Mutations of SDHA (p < 0.01), ERBB2 (p < 0.01), and ESR1 (p < 0.05) were negatively correlated with age, and mutations of NF1 (p < 0.01), KRAS (p < 0.01), and TP53 (p < 0.001) were significantly associated with gender.

CONCLUSIONS

This work revealed the mutational landscape and characteristics of 30 core driver genes in a LUAD cohort. Co-mutated genes and genes associated with gender and age indicate their different roles in the corresponding subgroup of the LUAD.

LRP1 involvement in FHIT-regulated HER2 signaling in non-small cell lung cancer

The tumor suppressor fragile histidine triad (FHIT) is frequently lost in non-small cell lung cancer (NSCLC). We previously showed that a down-regulation of FHIT causes an up-regulation of the activity of HER2 associated to an epithelial-mesenchymal transition (EMT) and that lung tumor cells harboring a FHITlow/pHER2high phenotype are sensitive to anti-HER2 drugs. Here, we sought to decipher the FHIT-regulated HER2 signaling pathway in NSCLC. Transcriptomic analysis of tumor cells isolated from NSCLC revealed the endocytic receptor low density lipoprotein receptor-related protein 1 (LRP1), a central regulator of membrane trafficking and cell signaling, as a potential player of this signaling. In a cohort of 80 NSCLC assessed by immunohistochemistry, we found a significant association between a low FHIT expression and a high pHER2 and LRP1 expression by tumor cells. Experiments of FHIT silencing showed that FHIT regulated LRP1 expression both at the mRNA and protein levels in lung cell lines. Analyzing the relationship between LRP1 and HER2, we observed that an anti-HER2 targeted therapy reversed LRP1 overexpression induced by FHIT silencing whereas LRP1 silencing did not affect HER2 activity. Studying the functional role of LRP1, we showed that cell proliferation and invasion induced by FHIT silencing were LRP1-dependent. In addition, we found that the induction of vimentin upon FHIT inactivation was counteracted by LRP1 silencing. These results suggest that LRP1 acts downstream of HER2 to induce EMT and tumor progression following FHIT loss. Dual targeting of HER2 and LRP1 might represent a therapeutic strategy to more efficiently inhibit HER2 signaling in FHIT-negative NSCLC.

SSBP1 positively regulates RRM2, affecting epithelial mesenchymal transition and cell cycle arrest in human lung adenocarcinoma cells

Progression of lung adenocarcinoma (LUAD) is frequently associated with alterations in epithelial-mesenchymal transition (EMT) and cell cycle. Our study analyzed the Cancer Genome Atlas (TCGA) database and identified a positive correlation between high expression of SSBP1 in LUAD tumor tissues and poor prognosis (p < 0.05), with an AUC of 0.853, suggesting that SSBP1 could serve as a prognostic biomarker. In vitro experiments, including siRNA-mediated SSBP1 knockdown and subsequent cell cloning and Transwell assays, revealed significant inhibition of proliferation, migration, and cell cycle progression in LUAD cells (p < 0.05). In vivo mouse model experiments further confirmed that SSBP1 knockdown inhibits tumor burden (p < 0.05). Mechanistic investigations, integrating pathway enrichment analysis with molecular biology techniques, identified RRM2 as a downstream target of SSBP1, and RRM2 knockdown similarly suppressed LUAD cell proliferation, migration, and cell cycle progression (p < 0.05). These findings indicate that SSBP1 promotes EMT and cell cycle progression in LUAD cells by positively regulating RRM2, thereby accelerating disease progression. Collectively, our study not only confirms the potential role of SSBP1 in LUAD but also provides a theoretical foundation for therapeutic strategies targeting the SSBP1/RRM2 axis, potentially offering new therapeutic targets for LUAD patients.

Solid Predominant Histology and High Podoplanin Expression in Cancer-Associated Fibroblast Predict Primary Resistance to Osimertinib in EGFR-Mutated Lung Adenocarcinoma

Introduction

Resistance to EGFR tyrosine kinase inhibitors is influenced by tumor-intrinsic and -extrinsic factors. We investigated the impact of tumor cell histology and tumor microenvironment on the efficacy of osimertinib.

Methods

We evaluated surgically resected adenocarcinoma from patients treated with first-line osimertinib at the National Cancer Center Hospital East (2016-2023), evaluating clinicopathologic characteristics, tumor cell histology, podoplanin expression in cancer-associated fibroblasts (CAFs) identified by immunohistochemistry, and outcomes. We also investigated HGF mRNA expression levels, using The Cancer Genome Atlas Program and Singapore Oncology Data Portal cohorts.

Results

The study included 93 patients. Solid (n = 19) versus non-solid predominant (n = 74) histology was not associated with worse disease-free survival after surgery (p = 0.12), but was significantly associated with worse progression-free survival (PFS) and overall survival following osimertinib treatment (p = 0.026, p = 0.004). Similarly, high-podoplanin (n = 31) versus low-podoplanin (n = 62) expression in CAFs was not associated with worse disease-free survival after surgery (p = 0.65), but was significantly associated with worse PFS and showed a trend towards worse overall survival following osimertinib treatment (p < 0.001, p = 0.11). In the multivariable analysis, solid predominant histology and high-podoplanin expression in CAFs were independently associated with worse PFS. In the cohorts of The Cancer Genome Atlas Program and Singapore Oncology Data Portal, EGFR-mutated lung adenocarcinoma with solid predominant histology or high-podoplanin expression exhibited significantly higher HGF expression.

Conclusions

Solid predominant histology and high-podoplanin expression in CAFs predicted osimertinib resistance, potentially guiding the selection of patients for more intensive treatments beyond osimertinib monotherapy.

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.

Impact of histopathological subtypes on invasive lung adenocarcinoma: from epidemiology to tumour microenvironment to therapeutic strategies

Lung adenocarcinoma is the most prevalent type of lung cancer, with invasive lung adenocarcinoma being the most common subtype. Screening and early treatment of high-risk individuals have improved survival; however, significant differences in prognosis still exist among patients at the same stage, especially in the early stages. Invasive lung adenocarcinoma has different histological morphologies and biological characteristics that can distinguish its prognosis. Notably, several studies have found that the pathological subtypes of invasive lung adenocarcinoma are closely associated with clinical treatment. This review summarised the distribution of various pathological subtypes of invasive lung adenocarcinoma in the population and their relationship with sex, smoking, imaging features, and other histological characteristics. We comprehensively analysed the genetic characteristics and biomarkers of the different pathological subtypes of invasive lung adenocarcinoma. Understanding the interaction between the pathological subtypes of invasive lung adenocarcinoma and the tumour microenvironment helps to reveal new therapeutic targets for lung adenocarcinoma. We also extensively reviewed the prognosis of various pathological subtypes and their effects on selecting surgical methods and adjuvant therapy and explored future treatment strategies.

Distribution of EGFR and KRAS Mutations in Patients with Surgically Resected Non-Small Cell Lung Cancer from Southern Italy: Real-Life Data from a Single Institution and Literature Review

BACKGROUND/OBJECTIVES

The identification of driver mutations in NSCLC such as those in the EGFR and KRAS genes has revolutionized the understanding and management of many lung cancer patients and has opened up a new scenario in the early disease stages in terms of therapeutic options (EGFR) and prognosis (KRAS). Data on prevalence rates and disease stage distributions of EGFR and KRAS mutations in surgically resected NSCLC are growing, but in Southern Italy, estimation is limited, since upfront EGFR testing in early-stage adenocarcinoma has been only recently introduced according to the current guidelines in clinical practice, whereas KRAS screening is usually uninvestigated in resected NSCLC. In this real-life study of a single institution in the Apulia Region, we provide an overview of the epidemiological distribution of EGFR and KRAS mutations in patients in Southern Italy with resected NSCLC, highlighting their prevalence, clinical significance, and correlation with demographic and pathological factors. A literature review was also performed to compare our findings with the most recent available data from the screening of Italian cohorts of advanced and surgically resected NSCLC patients.

METHODS

Data from 149 patients coming from Southern Italy with surgically resected NSCLC were retrospectively collected over a period of 16 years. EGFR and KRAS mutation screenings were performed and correlated with clinical and pathological data.

RESULTS

In total, 24 out of 149 NSCLC (16%) patients harbored an EGFR mutation. Exon 19 deletions and missense p.L858R mutations of the EGFR gene have quite similar frequencies (46%) and were more observed in never smokers (p < 0.001) and female (p < 0.001) patients with the adenocarcinoma histotype. KRAS gene mutations were detected in 31.5% of cases, with missense p.G12C (32%), p.G12V (28%), and p.G12D (17%) mutations as the most frequent ones. Neither EGFR nor KRAS mutational status were found to impact overall survival (OS) in our study cohort.

CONCLUSIONS

Our findings improve the understanding of lung cancer genetics in a small and homogeneous area of Southern Italy and guide future research. The EGFR and KRAS mutations in NSCLC resected patients from Southern Italy showed a global similar incidence compared to other recently described Italian cohorts of advanced and early-stage NSCLC, with a higher frequency of exon19 EGFR deletions. No prognostic impact was observed for both EGFR and KRAS status, but additional investigations on a larger cohort are needed.

Gene Mutation Characteristics and Prognostic Significance in Acute Myeloid Leukemia Patients From Northeast China

A great part of studies on the correlation between gene mutations and prognosis in acute myeloid leukemia (AML) patients are based on Western populations. To profile the genomic landscape of AML patients in Northeast China, we retrospectively analyzed the clinical data of 377 newly diagnosed AML patients in Shengjing Hospital of China Medical University from 2016 to 2022 and compared them with data from other populations with different genetic backgrounds. The mutation status of NPM1, FLT3-ITD, FLT3-TKD, CEBPA (CCAT enhancer binding protein alpha), ASXL1, TET2, KIT, DNMT3A (DNA methyltransferase 3A), IDH1, IDH2, EZH2 (enhancer of zeste 2), RUNX1, TP53, NRAS, and GATA2 was acquired by next-generation sequencing (NGS) technology; meanwhile, the clinical data of the patients were collected. The Cox regression model was used to analyze factors affecting patient survival and the impact of CEBPA and DNMT3A mutation on prognosis, and the results were different from those in other populations. Seventy-seven of 377 patients (20.4%) were detected with CEBPA mutations, which was higher than the 2%-6% in the Caucasian population. In the CEBPAdm patients who did not receive bone marrow transplantation, the prognosis of male patients (n = 18) was significantly better than that of female patients (n = 21) (p = 0.0242). Sixty-three of 377 patients (16.7%) carried the DNMT3A mutation, which was lower than the mutation frequency of 20.9% in the German-Austrian population, and the prognosis of these patients was significantly poorer (p = 0.0052). In addition, the prognostic evaluation value of the DNMT3A mutation in AML patients was not affected regardless of the presence of the NPM1 and FLT3-ITD comutation (p > 0.05), nor the mutation site of DNMT3A. In conclusion, for the Northeastern Chinese population, the prognosis of male patients with CEBPAdm was more favorable than that of female patients, and the DNMT3A mutation serves as an independent predictor of poor prognosis in AML. These results highlighted the central role of genetic background in precision medicine strategies and further emphasized the importance of the clinical characteristics of AML gene mutations in the Chinese population.

Effects of Tp53 Gene Mutations on the Survival of Non-Small Cell Lung Cancer (NSCLC); A Short Review

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Mutations within the TP53 gene represent critical molecular events in NSCLC, contributing to the tumorigenesis in the pulmonary epithelial tissues. TP53 is a widely researched prognostic indicator in NSCLC, and pathological investigations have revealed a weak to mild negative predictive effect for TP53. Mutated p53 protein may have some pro-oncogenic impact, and the variations may change tumor inhibitors into oncogenes. The diverse mutational spectrum of TP53 in NSCLC with different mutations is linked to varied treatment responses. In contrast, first-line chemotherapeutics to this progress are limited, however, randomized trials with new chemotherapeutics have shown significant survival benefits. This review highlighted the critical influence of TP53 gene mutations on pathological-sensitivity and overall survival outcomes in NSCLC. Further research is needed to explore TP53 mutation-specific pathways and their effects on NSCLC progression and treatment effectiveness.

Optimizing the NGS-based discrimination of multiple lung cancers from the perspective of evolution

Next-generation sequencing (NGS) offers a promising approach for differentiating multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), though panel selection and clonal interpretation remain challenging. Whole-exome sequencing (WES) data from 80 lung cancer samples were utilized to simulate MPLC and IPM, with various sequenced panels constructed through gene subsampling. Two clonal interpretation approaches primarily applied in clinical practice, MoleA (based on shared mutation comparison) and MoleB (based on probability calculation), were subsequently evaluated. ROC analysis highlighted MoleB's superior performance, especially with the NCCNplus panel (AUC = 0.950 ± 0.002) and pancancer MoleA (AUC = 0.792 ± 0.004). In two independent cohorts (WES cohort, N = 42 and non-WES cohort, N = 94), NGS-based methodologies effectively stratified disease-free survival, with NCCNplus MoleB further predicting prognosis. Phylogenetic analysis further revealed evolutionary distinctions between MPLC and IPM, establishing an optimized NGS-based framework for differentiating multiple lung cancers.

Evaluation of the efficacy of PD‑1/PD‑L1 inhibitor plus bevacizumab and chemotherapy for the treatment of patients with driver gene‑negative advanced‑stage lung adenocarcinoma: A retrospective cohort study

Driver gene-negative advanced-stage lung adenocarcinoma is associated with a poor prognosis and insufficient treatment options. The present study aimed to evaluate the efficacy and safety profile of a programmed cell death protein 1/programmed death-ligand 1 inhibitor plus bevacizumab and chemotherapy (PBC) regimen for the treatment of patients with driver gene-negative advanced-stage lung adenocarcinoma under real-world clinical conditions. Data from 65 patients with advanced-stage lung adenocarcinoma without sensitizing epidermal growth factor receptor, ALK receptor tyrosine kinase or ROS proto-oncogene 1 receptor tyrosine kinase mutations who received a PBC regimen or only a BC regimen were reviewed in the present retrospective cohort study. The results revealed that the objective response rate was higher (70.4 vs. 47.4%; P=0.065) in the PBC group compared with that in the BC group, while not reaching statistical significance. Progression-free survival (PFS) time was longer in the PBC group than in the BC group [median PFS: 10.8 months (95% confidence interval (CI), 7.2-14.4) vs. 7.6 months (95% CI, 5.0-10.2); P=0.016], while overall survival (OS) exhibited a non-significant trend to be longer in the PBC group compared with that in the BC group [median OS: 20.6 months (95% CI, 16.8-24.4) vs. 15.9 months (95% CI, 11.8-20.0); P=0.115]. Following adjustment by multivariate Cox analysis, the PBC (vs. BC) regimen was found to be independently associated with an improved PFS time (P=0.045). The common adverse events in the PBC group were neutropenia, alopecia, leukopenia, nausea and vomiting, fatigue, anemia and peripheral neuropathy. Moreover, the incidence of each adverse event did not differ significantly between the PBC and BC groups. In conclusion, the present study demonstrated that the PBC regimen serves as a superior treatment option for patients with driver gene-negative advanced-stage lung adenocarcinoma; however, further verification of its efficacy is still required.

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.

Tumor Mutation Signature Reveals the Risk Factors of Lung Adenocarcinoma with EGFR or KRAS Mutation

INTRODUCTION

EGFR and KRAS mutations are frequently detected in lung adenocarcinoma (LUAD). Tumor mutational signature (TMS) determination is an approach to identify somatic mutational patterns associated with pathogenic factors. In this study, through the analysis of TMS, the underlying pathogenic factors of LUAD with EGFR and KRAS mutations were traced.

METHODS

This was a retrospective study. TMS of LUAD with KRAS and EGFR mutations from the TCGA, OncoSG, and MSK datasets was determined by two bioinformatics tools, namely the "MutationalPatterns" and "FitMS" packages. Elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) of LUAD clinical specimens was analyzed using capillary electrophoresis.

RESULTS

In LUAD with KRAS mutations, TMS analysis indicated that the smoking-related SBS4 signature was enriched. For LUAD with EGFR L858R mutation, the smoking-related SBS4 signature was enriched in the Western population from the TCGA database; however, the smoking-related SBS4 signature was not obvious in Asian LUAD patients. LUAD with EGFR exon19 deletion (19Del) exhibited stronger SBS15 signature, which was related to defective DNA mismatch repair. Capillary electrophoresis analysis showed that an EMAST locus was frequently instable in LUAD with EGFR 19Del. Different from the Western population, Asian LUAD patients with EGFR mutations exhibited the enrichment of SBS1, SBS2, and SBS13 signatures, which were associated with the endogenous mutation process of cytidine deamination.

CONCLUSIONS

TMS analysis reveals that smoking is associated with LUAD with KRAS mutations. Defective DNA mismatch repair and endogenous cytidine deamination are associated with LUAD with EGFR mutations, especially for the EGFR 19Del. The endogenous mutational process is stronger in Asian LUAD patients than Western LUAD patients.

Identify Non-mutational p53 Functional Deficiency in Human Cancers

An accurate assessment of p53's functional statuses is critical for cancer genomic medicine. However, there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA sequencing. These undetected cases are often misclassified as p53-normal, leading to inaccurate prognosis and downstream association analyses. To address this issue, we built the support vector machine (SVM) models to systematically reassess p53's functional statuses in TP53 wild-type (TP53WT) tumors from multiple The Cancer Genome Atlas (TCGA) cohorts. Cross-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve (AUROC) of 0.9822, precision of 0.9747, and recall of 0.9784. Our study revealed that a significant proportion (87%-99%) of TP53WT tumors actually had compromised p53 function. Additional analyses uncovered that these genetically intact but functionally impaired (termed as predictively reduced function of p53 or TP53WT-pRF) tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors: heightened genomic instability and elevated levels of hypoxia. Clinically, patients with TP53WT-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53 (TP53WT-pN) tumors, and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

MAZ promotes tumor proliferation and immune evasion in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most dominant histological subtype of lung cancer and one of the most lethal malignancies. The identification of novel therapeutic targets is required for the treatment of LUAD. Here, we showed that MYC-associated zinc-finger protein (MAZ) is upregulated in LUAD tissues. MAZ expression levels are inversely correlated with patient survival. Silencing of MAZ decreased tumor proliferation and the expression of pro-tumorigenic chemokines and Galectin-9 (Gal-9), an immune checkpoint molecule. The pro-tumorigenic chemokines and Gal-9 induce immune suppression by recruitment of myeloid cells and inhibition of T cell activation, respectively. Mechanistically, MAZ transcriptionally regulates KRAS expression and activates its downstream AKT-NF-κB signaling pathway, which is crucial for tumor progression and immune evasion. Additionally, in vivo animal models and bioinformatic analyses indicated that MAZ suppression could enhance the efficacy of immune checkpoint blockade (ICB) therapy for LUAD. Overall, our results suggest that MAZ plays an important role in regulating cell proliferation and immune evasion via KRAS/AKT/NF-κB signaling in LUAD. Our findings offer a candidate molecular target for LUAD therapy, with implications for improving the efficacy of ICB therapy.

A Core NRF2 Gene Set Defined Through Comprehensive Transcriptomic Analysis Predicts Selective Drug Resistance and Poor Multicancer Prognosis

Aims: The nuclear factor erythroid 2-related factor 2-Kelch-like ECH-associated protein 1 (NRF2-KEAP1) pathway plays an important role in the cellular response to oxidative stress but may also contribute to metabolic changes and drug resistance in cancer. However, despite its pervasiveness and important role, most of nuclear factor erythroid 2-related factor 2 (NRF2) target genes are defined in context-specific experiments and analysis, making it difficult to translate from one situation to another. Our study investigates whether a core NRF2 gene signature can be derived and used to represent NRF2 activation in various contexts, allowing better reproducibility and understanding of NRF2. Results: We define a core set of 14 upregulated NRF2 target genes from 7 RNA-sequencing datasets that we generated and analyzed. This NRF2 gene signature was validated using analyses of published datasets and gene sets. An NRF2 activity score based on expression of these core target genes correlates with resistance to drugs such as PX-12 and necrosulfonamide but not to paclitaxel or bardoxolone methyl. We validated these findings in our Kelch-like ECH-associated protein 1 (KEAP1) knockout cancer cell lines. Finally, our NRF2 score is prognostic for cancer survival and validated in additional independent cohorts for lung adenocarcinoma and also novel cancer types not associated with NRF2-KEAP1 mutations such as clear cell renal carcinoma, hepatocellular carcinoma, and acute myeloid leukemia. Innovation and Conclusions: These analyses define a core NRF2 gene signature that is robust, versatile, and useful for evaluating NRF2 activity and for predicting drug resistance and cancer prognosis. Using this gene signature, we uncovered novel selective drug resistance and cancer prognosis associated with NRF2 activation. Antioxid. Redox Signal. 41, 1031-1050.

Integrative study of lung cancer adeno-to-squamous transition in EGFR TKI resistance identifies RAPGEF3 as a therapeutic target

Although adeno-to-squamous transition (AST) has been observed in association with resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) in clinic, its causality, molecular mechanism and overcoming strategies remain largely unclear. We here demonstrate that squamous transition occurs concomitantly with TKI resistance in PC9-derived xenograft tumors. Perturbation of squamous transition via DNp63 overexpression or knockdown leads to significant changes in TKI responses, indicative of a direct causal link between squamous transition and TKI resistance. Integrative RNA-seq, ATAC-seq analyses and functional studies reveal that FOXA1 plays an important role in maintaining adenomatous lineage and contributes to TKI sensitivity. FOXM1 overexpression together with FOXA1 knockout fully recapitulates squamous transition and TKI resistance in both PC9 xenografts and patient-derived xenograft (PDX) models. Importantly, pharmacological inhibition of RAPGEF3 combined with EGFR TKI efficiently overcomes TKI resistance, especially in RAPGEF3high PDXs. Our findings provide novel mechanistic insights into squamous transition and therapeutic strategy to overcome EGFR TKI resistance in lung cancer.

Landscape of Clinically Relevant Genomic Alterations in the Indian Non-small Cell Lung Cancer Patients

BACKGROUND

The genomic landscape of non-small cell lung cancer (NSCLC) in the Indian patients remains underexplored. We revealed distinctive genomic alterations of Indian NSCLC patients, thereby providing vital molecular insights for implementation of precision therapies.

METHODS

We analyzed the genomic profiles of 325 lung adenocarcinoma and 81 lung squamous carcinoma samples from Indian patients using targeted sequencing of 50 cancer related genes. Correlations between genomic alterations and clinical characteristics were computed using statistical analyses. Additionally, we identified distinct features of Indian NSCLC genomes by comparison across different ethnicities.

RESULTS

Our genomic analysis revealed several noticeable features of Indian NSCLC patients. Alterations in EGFR (45.8%), TP53 (27.4%), ALK (11.4%) and KRAS (10.2%) were predominant in adenocarcinoma, with 68% eligible for targeted therapies. Squamous carcinoma exhibited prevalent alterations in TP53 (40.7%), PIK3CA (17.3%), and CDKN2A (8.6%). We observed higher frequency of EGFR alterations (18.5%) in lung squamous carcinoma patients, significantly distinct from other ethnicities reported till date. Beyond established correlations, we observed 60% of PD-L1 negative squamous patients harbored TP53 alterations, suggesting intriguing therapeutic implications.

CONCLUSIONS

Our data revealed unique genomic variations of adenocarcinoma and squamous carcinoma patients, with significant indications for precision medicine and clinical practice of lung cancers. The study emphasizes the importance of clinical utility of NGS for routine diagnostics.

Lung-MAP Next-Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400)

INTRODUCTION

Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, that is, by next-generation sequencing (NGS), is needed to identify potential targets. Lung Cancer Master Protocol Southwest Oncology Group S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic sub-studies.

METHODS

Tumors underwent NGS using Foundation Medicine's FoundationOne research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually exclusive gene set analysis and Selected Events Linked by Evolutionary Conditions across Human Tumors were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to assess associations between genetic variants and survival.

RESULTS

NGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. Mutually exclusive gene set analysis identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate of less than 15%: NFE2L2, KEAP1, and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R), and 3509C>T (T1170I). When taken together, NFE2L2 and KEAP1 alterations were associated with poorer survival.

CONCLUSIONS

As the largest dataset to date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance.

Mutation-guided chemotherapy-free strategy in first-line immunotherapy for low PD-L1-expressing non-squamous NSCLC

BACKGROUND

The necessity of platinum-doublet chemotherapy in first-line immunotherapy for non-squamous non-small cell lung cancer (nsqNSCLC) with programmed death-ligand 1 (PD-L1) expression on less than 50% of tumor cells remains poorly investigated. Biomarkers predicting this necessity can guide chemotherapy-free treatment to minimize unnecessary toxicity.

METHODS

Treated with immune checkpoint inhibitor monotherapy (ICI-mono), chemotherapy, or combination (ICI-chemo), 790 low PD-L1-expressing nsqNSCLCs (in-house: n=83; public: n=707) were analyzed for development and validation of the interaction score for additional chemotherapy (ISAC). Transcriptomic (public, n=11) and multiplex immunofluorescence data (in-house, n=100) were analyzed to evaluate the immune microenvironment.

RESULTS

ICI-chemo, compared with ICI-mono, tended to prolong progression-free survival (PFS; HR=0.72, p=0.004) and overall survival (OS; HR=0.77, p=0.071) as first-line therapy in low PD-L1-expressing nsqNSCLCs. The added value of chemotherapy was observed in the ISAC-low subgroup (PFS: HR=0.48, p<0.001; OS: HR=0.53, p=0.001) rather than the ISAC-high subgroup (PFS: HR=1.08, p=0.65; OS: HR=1.14, p=0.56). This predictive utility was independent of tumor mutational burden and PD-L1 expression, indicated by subgroup and multivariable analyses. A high ISAC was associated with adaptive immune resistance reflected by more proinflammatory (eg, CD8+ T cells and M1 macrophages) rather than anti-inflammatory tumor-infiltrating immune cells (eg, M2 macrophages) and high expression of immune checkpoints except for PD-L1 (eg, programmed cell death protein-1).

CONCLUSION

A high ISAC was identified as a significant predictor for virtually no added value of platinum-doublet chemotherapy for first-line ICI treatment in low PD-L1-expressing nsqNSCLC. Our findings may help refine personalized therapeutic strategies for nsqNSCLC, thereby improving efficacy and reducing undue toxicity.

Integrated proteomic and glycoproteomic analysis reveals heterogeneity and molecular signatures of brain metastases from lung adenocarcinomas

Brain metastasis is a major cause of poor prognosis and death in lung adenocarcinoma (LUAD); however, the understanding of therapeutic strategies and mechanisms for brain metastases from LUAD (BM-LUAD) remains notably limited, especially at the proteomics levels. To address this issue, we conducted integrated proteomic and glycoproteomic analyses on 49 BM-LUAD tumors, revealing two distinct subtypes of the disease: BM-S1 and BM-S2. Whole exome sequencing analysis revealed that somatic mutations in STK11 and KEAP1, as well as copy number deletions on chr19p13.3, such as STK11, UQCR11, and SLC25A23, were more frequently detected in BM-S2. In BM-S1 tumors, we observed significant infiltration of GFAP + astrocytes, as evidenced by elevated levels of GFAP, GABRA2, GABRG1 and GAP43 proteins and an enrichment of astrocytic signatures in both our proteomic data and external spatial transcriptomic data. Conversely, BM-S2 tumors demonstrated higher levels of PD-1 immune cell infiltration, supported by the upregulation of PD-1 and LAG-3 genes. These findings suggest distinct microenvironmental adaptations required by the different BM-LUAD subtypes. Additionally, we observed unique glycosylation patterns between the subtypes, with increased fucosylation in BM-S1 and enhanced sialylation in BM-S2, primarily affected by glycosylation enzymes such as FUT9, B4GALT1, and ST6GAL1. Specifically, in BM-S2, these sialylation modifications are predominantly localized to the lysosomes, underscoring the critical role of N-glycosylation in the tumor progression of BM-LUAD. Overall, our study not only provides a comprehensive multi-omic data resource but also offers valuable biological insights into BM-LUAD, highlighting potential mechanisms and therapeutic targets for further investigation.

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Background

Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.

Methods

Data on clinical and pathological characteristics, genetic alterations, DNA methylation patterns, and the expression of mRNA, lncRNA, and microRNA, along with somatic mutations in LUAD patients, were gathered from the TCGA and GEO datasets. A computational workflow was utilized to merge multi-omics data from LUAD patients through 10 clustering techniques, which were paired with 10 machine learning methods to pinpoint detailed molecular subgroups and refine a prognostic risk model. The disparities in somatic mutations, copy number alterations, and immune cell infiltration between high- and low-risk groups were assessed. The effectiveness of immunotherapy in patients was evaluated through the TIDE and SubMap algorithms, supplemented by data from various immunotherapy groups. Furthermore, the Cancer Therapeutics Response Portal (CTRP) and the PRISM Repurposing dataset (PRISM) were employed to investigate new drug treatment approaches for LUAD. In the end, the role of SLC2A1 in tumor dynamics was examined using RT-PCR, immunohistochemistry, CCK-8, wound healing, and transwell tests.

Results

By employing multi-omics clustering, we discovered two unique cancer subtypes (CSs) linked to prognosis, with CS2 demonstrating a better outcome. A strong model made up of 17 genes was created using a random survival forest (RSF) method, which turned out to be an independent predictor of overall survival and showed reliable and impressive performance. The low-risk group not only had a better prognosis but also was more likely to display the "cold tumor" phenotype. On the other hand, individuals in the high-risk group showed a worse outlook and were more likely to respond positively to immunotherapy and six particular chemotherapy medications. Laboratory cell tests demonstrated that SLC2A1 is abundantly present in LUAD tissues and cells, greatly enhancing the proliferation and movement of LUAD cells.

Conclusions

Thorough examination of multi-omics data offers vital understanding and improves the molecular categorization of LUAD. Utilizing a powerful machine learning system, we highlight the immense potential of the riskscore in providing individualized risk evaluations and customized treatment suggestions for LUAD patients.

DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment

Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor microenvironments. Despite challenges due to heterogeneity within and among tumors, our innovative deep learning-based approach, DeSide, shows exceptional accuracy in estimating the proportions of 16 distinct cell types and subtypes within solid tumors. DeSide integrates biological pathways and assesses noncancerous cell types first, effectively sidestepping the issue of highly variable gene expression profiles (GEPs) associated with cancer cells. By leveraging scRNA-seq data from six cancer types and 185 cancer cell lines across 22 cancer types as references, our method introduces distinctive sampling and filtering techniques to generate a high-quality training set that closely replicates real tumor GEPs, based on The Cancer Genome Atlas (TCGA) bulk RNA-seq data. With this model and high-quality training set, DeSide outperforms existing methods in estimating tumor purity and the proportions of noncancerous cells within solid tumors. Our model precisely predicts cellular compositions across 19 cancer types from TCGA and proves its effectiveness with multiple additional external datasets. Crucially, DeSide enables the identification and analysis of combinatorial cell type pairs, facilitating the stratification of cancer patients into prognostically significant groups. This approach not only provides deeper insights into the dynamics of tumor biology but also highlights potential therapeutic targets by underscoring the importance of specific cell type or subtype interactions.

Gene expression-based modeling of overall survival in Black or African American patients with lung adenocarcinoma

Introduction

Lung cancer is a leading cause of cancer-related deaths worldwide. Black/African American (B/AA) populations, in particular, exhibit the highest incidence and mortality rates of lung adenocarcinoma (LUAD) in the United States.

Methods

This study aims to explore gene expression patterns linked to LUAD in B/AA and case-matched white patients, with the goal of developing predictive models for prognosis. Leveraging RNA sequencing data from The Cancer Genome Atlas (TCGA) database, genes and pathways associated with overall survival (OS) were identified.

Results

The OS-associated genes in B/AA patients were distinct from those in white patients, showing predominant enrichment in immune-related pathways. Furthermore, mRNA co-expression network analysis revealed that OS-associated genes in B/AA patients had higher levels of interaction with various pathways, including those related to immunity, cell-ECM interaction, and specific intracellular signaling pathways. Notably, a potential B/AA-specific biomarker, C9orf64, demonstrated significant correlations with genes involved in immune response. Unsupervised machine learning algorithms stratified B/AA patients into groups with distinct survival outcomes, while supervised algorithms demonstrated a higher accuracy in predicting survival for B/AA LUAD patients compared to white patients.

Discussion

In total, this study explored OS-associated genes and pathways specific for B/AA LUAD patients. Further validation and clinical application of these findings are warranted to address disparities and improve outcomes in diverse patient populations.

Research progress on the role of bypass activation mechanisms in resistance to tyrosine kinase inhibitors in non-small cell lung cancer

The clinical application of small molecule tyrosine kinase inhibitors (TKIs) has significantly improved the quality of life and prognosis of patients with non-small cell lung cancer (NSCLC) carrying driver genes. However, resistance to TKI treatment is inevitable. Bypass signal activation is one of the important reasons for TKI resistance. Although TKI drugs inhibit downstream signaling pathways of driver genes, key signaling pathways within tumor cells can still be persistently activated through bypass routes such as MET gene amplification, EGFR gene amplification, and AXL activation. This continuous activation maintains tumor cell growth and proliferation, leading to TKI resistance. The fundamental strategy to treat TKI resistance mediated by bypass activation involves simultaneously inhibiting the activated bypass signals and the original driver gene signaling pathways. Some clinical trials based on this combined treatment approach have yielded promising preliminary results, offering more treatment options for NSCLC patients with TKI resistance. Additionally, early identification of resistance mechanisms through liquid biopsy, personalized targeted therapy against these mechanisms, and preemptive targeting of drug-tolerant persistent cells may provide NSCLC patients with more sustained and effective treatment.

Ferroptosis-related gene signature for predicting prognosis and identifying potential therapeutic drug in EGFR wild-type lung adenocarcinoma

Epidermal growth factor receptor wild type lung adenocarcinoma (EGFRWT LUAD) still has limited treatment options and unsatisfactory clinical outcomes. Ferroptosis, as a form of cell death, has been reported to play a dual role in regulating tumor cell survival. In this study, we constructed a 3-ferroptosis-gene signature, FeSig, and verified its accuracy and efficacy in predicting EGFRWT LUAD prognosis at both the RNA and protein levels. Patients with higher FeSig scores were found to have worse clinical outcomes. Additionally, we explored the relationship between FeSig and tumor microenvironment, revealing that enhanced interactions between fibroblasts and tumor cells in FeSighigh patients causing tumor resistance to ferroptosis. To address this challenge, we screened potential drugs from NCI-60 (The US National Cancer Institute 60 human tumour cell line anticancer drug screen) and Connectivity map database, ultimately identifying 6-mercatopurine (6-MP) as a promising candidate. Both in vitro and in vivo experiments demonstrated its efficacy in treating FeSighigh EGFRWT LUAD tumor models. In summary, we develop a novel FeSig for predicting prognosis and guiding drug application.

Spatial immunogenomic patterns associated with lymph node metastasis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) with lymph node (LN) metastasis is linked to poor prognosis, yet the underlying mechanisms remain largely undefined. This study aimed to elucidate the immunogenomic landscape associated with LN metastasis in LUAD.

METHODS

We employed broad-panel next-generation sequencing (NGS) on a cohort of 257 surgically treated LUAD patients to delineate the molecular landscape of primary tumors and identify actionable driver-gene alterations. Additionally, we used multiplex immunohistochemistry (mIHC) on a propensity score-matched cohort, which enabled us to profile the immune microenvironment of primary tumors in detail while preserving cellular metaclusters, interactions, and neighborhood functional units. By integrating data from NGS and mIHC, we successfully identified spatial immunogenomic patterns and developed a predictive model for LN metastasis, which was subsequently validated independently.

RESULTS

Our analysis revealed distinct immunogenomic alteration patterns associated with LN metastasis stages. Specifically, we observed increased mutation frequencies in genes such as PIK3CG and ATM in LN metastatic primary tumors. Moreover, LN positive primary tumors exhibited a higher presence of macrophage and regulatory T cell metaclusters, along with their enriched neighborhood units (p < 0.05), compared to LN negative tumors. Furthermore, we developed a novel predictive model for LN metastasis likelihood, designed to inform non-surgical treatment strategies, optimize personalized therapy plans, and potentially improve outcomes for patients who are ineligible for surgery.

CONCLUSIONS

This study offers a comprehensive analysis of the genetic and immune profiles in LUAD primary tumors with LN metastasis, identifying key immunogenomic patterns linked to metastatic progression. The predictive model derived from these insights marks a substantial advancement in personalized treatment, underscoring its potential to improve patient management.

Proteogenomic analysis of air-pollution-associated lung cancer reveals prevention and therapeutic opportunities

Air pollution significantly impacts lung cancer progression, but there is a lack of a comprehensive molecular characterization of clinical samples associated with air pollution. Here, we performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC cohort), where coal smoke is the primary contributor to the high lung cancer incidence. Genomic mutation analysis revealed XWLC as a distinct subtype of LUAD separate from cases associated with smoking or endogenous factors. Mutational signature analysis suggested that Benzo[a]pyrene (BaP) is the major risk factor in XWLC. The BaP-induced mutation hotspot, EGFR-G719X, was present in 20% of XWLC which endowed XWLC with elevated MAPK pathway activations and worse outcomes compared to common EGFR mutations. Multi-omics clustering of XWLC identified four clinically relevant subtypes. These subgroups exhibited distinct features in biological processes, genetic alterations, metabolism demands, immune landscape, and radiomic features. Finally, MAD1 and TPRN were identified as novel potential therapeutic targets in XWLC. Our study provides a valuable resource for researchers and clinicians to explore prevention and treatment strategies for air-pollution-associated lung cancers.

Super multiple primary lung cancers harbor high-frequency BRAF and low-frequency EGFR mutations in the MAPK pathway

The incidence of multiple primary lung cancer (MPLC) is increasing, with some of our surgical patients exhibiting numerous lesions. We defined lung cancer with five or more primary lesions as super MPLCs. Elucidating the genomic characteristics of this special MPLC subtype can help reduce disease burden and understand tumor evolution. In our cohort of synchronous super early-stage MPLCs (PUMCH-ssesMPLC), whole-exome sequencing on 130 resected malignant specimens from 18 patients provided comprehensive super-MPLC genomic landscapes. Mutations are enriched in PI3k-Akt and MAPK pathways. Their BRAF mutation frequency (31.5%) is significantly higher than MPLC with fewer lesions and early-stage single-lesion cancer, while EGFR mutations are significantly fewer (13.8%). As lesion counts increase, BRAF mutations gradually become dominant. Also, invasive lesions more tend to have classic super-MPLC mutation patterns. High-frequency BRAF mutations, especially Class II, and low-frequency EGFR mutations could be a reason for the limited effectiveness of targeted therapy in super-MPLC patients.

Subclassification of lung adenocarcinoma through comprehensive multi-omics data to benefit survival outcomes

OBJECTIVES

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of great clinical significance. This study aims to identify novel molecular markers associated with LUAD subtypes, with the goal of improving the precision of LUAD subtype classification. Additionally, optimization efforts are directed towards enhancing insights from the perspective of patient survival analysis.

MATERIALS AND METHODS

We propose an innovative feature-selection approach that focuses on LUAD classification, which is comprehensive and robust. The proposed method integrates multi-omics data from The Cancer Genome Atlas (TCGA) and leverages a synergistic combination of max-relevance and min-redundancy, least absolute shrinkage and selection operator, and Boruta algorithms. These selected features were deployed in six machine-learning classifiers: logistic regression, random forest, support vector machine, naive Bayes, k-Nearest Neighbor, and XGBoost.

RESULTS

The proposed approach achieved an area under the receiver operating characteristic curve (AUC) of 0.9958 for LR. Notably, the accuracy and AUC of a composite model incorporating copy number, methylation, as well as RNA- sequencing data for expression of exons, genes, and miRNA mature strands surpassed the accuracy and AUC metrics of models with single-omics data or other multi-omics combinations. Survival analyses, revealed the SVM classifier to elicit optimal classification, outperforming that achieved by TCGA. To enhance model interpretability, SHapley Additive exPlanations (SHAP) values were utilized to elucidate the impact of each feature on the predictions. Gene Ontology (GO) enrichment analysis identified significant biological processes, molecular functions, and cellular components associated with LUAD subtypes.

CONCLUSION

In summary, our feature selection process, based on TCGA multi-omics data and combined with multiple machine learning classifiers, proficiently identifies molecular subtypes of lung adenocarcinoma and their corresponding significant genes. Our method could enhance the early detection and diagnosis of LUAD, expedite the development of targeted therapies and, ultimately, lengthen patient survival.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential.

METHOD

We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD.

RESULTS

We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways.

CONCLUSIONS

Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD.

RNA sequencing identifies lung cancer lineage and facilitates drug repositioning

Recent breakthrough therapies have improved survival rates in non-small cell lung cancer (NSCLC), but a paradigm for prospective confirmation is still lacking. Patientdatasets were mainly downloaded from TCGA, CPTAC and GEO. We conducted downstream analysis by collecting metagenes and generated 42-gene subtype classifiers to elucidate biological pathways. Subsequently, scRNA, eRNA, methylation, mutation, and copy number variation were depicted from a phenotype perspective. Enhancing the clinical translatability of molecular subtypes, preclinical models including CMAP, CCLE, and GDSC were utilized for drug repositioning. Importantly, we verified the presence of previously described three phenotypes including bronchioid, neuroendocrine, and squamoid. Poor prognosis was seen in squamoid and neuroendocrine clusters for treatment-naive and immunotherapy populations. The neuroendocrine cluster was dominated by STK11 mutations and 14q13.3 amplifications, whose related methylated loci are predictive of immunotherapy. And the greatest therapeutic potential lies in the bronchioid cluster. We further estimated the relative cell abundance of the tumor microenvironment (TME), specific cell types could be reflected among three clusters. Meanwhile, the higher portion of immune cell infiltration belonged to bronchioid and squamoid, not the neuroendocrine cluster. In drug repositioning, MEK inhibitors resisted bronchioid but were squamoid-sensitive. To conceptually validate compounds/targets, we employed RNA-seq and CCK-8/western blot assays. Our results indicated that dinaciclib and alvocidib exhibited similar activity and sensitivity in the neuroendocrine cluster. Also, a lineage factor named KLF5 recognized by inferred transcriptional factors activity could be suppressed by verteporfin.

Lung cancer screening in never smokers

PURPOSE OF REVIEW

Low-dose computed tomography (LDCT) lung cancer screening has been established in smokers, but its role in never smokers remains unclear. The differences in lung cancer biology between smokers and nonsmokers highlight the importance of a discriminated approach. This overview focuses on the emerging data and implementation challenges for LDCT screening in nonsmokers.

RECENT FINDINGS

The first LDCT screening study in nonsmokers enriched with risk factors demonstrated a lung cancer detection rate double that of the phase 3 trials in smokers. The relative risk of lung cancer detected by LDCT has also been found to be similar amongst female never smokers and male ever smokers in Asia. Majority of lung cancers detected through LDCT screening are stage 0/1, leading to concerns of overdiagnosis. Risk prediction models to enhance individual selection and nodule management could be useful to enhance the utility of LDCT screening in never smokers.

SUMMARY

With appropriate risk stratification, LDCT screening in never smokers may attain similar efficacy as compared to smokers. A global effort is needed to generate evidence surrounding optimal screening strategies, as well as health and economic benefits to determine the suitability of widespread implementation.