NSD2 dimethylation at H3K36 promotes lung adenocarcinoma pathogenesis.

The etiological role of NSD2 enzymatic activity in solid tumors is unclear. Here we show that NSD2, via H3K36me2 catalysis, cooperates with oncogenic KRAS signaling to drive lung adenocarcinoma (LUAD) pathogenesis. In vivo expression of NSD2E1099K, a hyperactive variant detected in individuals with LUAD, rapidly accelerates malignant tumor progression while decreasing survival in KRAS-driven LUAD mouse models. Pathologic H3K36me2 generation by NSD2 amplifies transcriptional output of KRAS and several complementary oncogenic gene expression programs. We establish a versatile in vivo CRISPRi-based system to test gene functions in LUAD and find that NSD2 loss strongly attenuates tumor progression. NSD2 knockdown also blocks neoplastic growth of PDXs (patient-dervived xenografts) from primary LUAD. Finally, a treatment regimen combining NSD2 depletion with MEK1/2 inhibition causes nearly complete regression of LUAD tumors. Our work identifies NSD2 as a bona fide LUAD therapeutic target and suggests a pivotal epigenetic role of the NSD2-H3K36me2 axis in sustaining oncogenic signaling.

Integrated machine learning survival framework to decipher diverse cell death patterns for predicting prognosis in lung adenocarcinoma.

Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and metastasis of tumors. Nevertheless, a comprehensive analysis of the diverse types of PCD in lung adenocarcinoma (LUAD) is currently lacking. The study encompassed a total of 1481 genes associated with the regulation of 13 distinct PCD patterns. Ten machine learning algorithms were amalgamated into 101 combinations, from which the optimal algorithm was chosen to formulate an artificial intelligence-derived prognostic signature based on the average C-index across four multicenter cohorts. The established optimal cell death index (CDI) model emerged as an independent risk factor for overall survival, demonstrating robust and consistent performance. Notably, CDI exhibited significantly higher accuracy compared to traditional clinical variables and molecular features. It exhibited superior performance than other published models. By integrating CDI with relevant clinical features, a nomogram with excellent predictive performance was developed. LUAD patients with low CDI score had a higher immune modulators, TIDE scores and immune scores, indicating a better immunotherapy benefit. More importantly, we found that the regulation of antigen presentation is the crucial mechanism of PCD. SCG2 is a key molecule that inhibits the malignant progression of LUAD. CDI holds great potential as a robust and promising tool for enhancing clinical outcomes in patients with LUAD.

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LUAD) being the most prevalent subtype. Given the high clinical and cellular heterogeneities of LUAD, accurate diagnosis and prognosis are crucial to avoid overdiagnosis and overtreatment. Taking full advantage of scRNA-Seq data to resolve the tumor heterogeneities, we explored the overall landscape of LUAD microenvironment. Utilizing the stage-specific tumor cell markers, we have developed highly accurate diagnostic and prognostic models with elevated sensitivity and specificity. The diagnostic model, developed through random forest algorithms with a thirteen-gene signature, achieved an accuracy of 96.4% and an AUC of 0.993. These metrics were further demonstrated by benchmarking with available models and scoring systems in independent cohorts. Concurrently, the prognostic model, formulated via Cox regression with a six-gene signature, effectively predicted overall survival, with elevated risk scores associated with increased fractions of cancer-associated fibroblasts, and higher likelihood of immune escape and T-cell exclusion. Subsequently, two nomograms were developed to predict survival and drug responses, facilitating their integration into clinical practice. Overall, this study underscores the potential of our models for efficient, rapid, and cost-effective diagnosis and prognosis of LUAD, adaptable to multiple expression profiling platforms and quantification methods.

The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma.

The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets.

BACKGROUND: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days. METHODS: Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets. RESULTS: Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options. CONCLUSIONS: We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.

Prognostic effect of TCF1+ CD8+ T cell and TOX+ CD8+ T cell infiltration in lung adenocarcinoma.

Recent studies have highlighted the pivotal roles of T cell transcription factors TCF-1 and TOX in modulating the immune response in cancer, with TCF-1 maintaining CD8+ T cell stemness and TOX promoting T cell exhaustion. The prognostic significance of these factors in lung adenocarcinoma (LUAD) remains a critical area of investigation. The retrospective study included 191 patients with LUAD who underwent surgery, of whom 83% were in stages II and III. These patients were divided into exploratory (n = 135) and validation (n = 56) groups based on the time of diagnosis. Multiplex fluorescence immunohistochemistry was used to examine the infiltration levels of CD8+ T cells, TCF1+ CD8+ T cells, and TOX+ CD8+ T cells. The percentage of CD8+ T cells in tumor was markedly lower than that in stroma (p < 0.05). In tumor-draining lymph nodes (TDLNs) invaded by tumor, the proportion of stem-like TCF1+ CD8+ T cells was significantly decreased (p < 0.01). Importantly, higher infiltration levels of CD8+ T cells and TCF1+ CD8+ T cells were associated with improved disease-free survival (DFS) (p = 0.009 and p = 0.006, respectively) and overall survival (OS) (p = 0.018 and p = 0.010, respectively). This study underscores the potential of TCF1+ CD8+ T cells as prognostic biomarkers in LUAD, providing insights into the tumor immune microenvironment and guiding future therapeutic strategies.

A novel cancer-associated fibroblasts risk score model predict survival and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Cancer-associated fibroblasts (CAFs) are a special type of fibroblasts, which play an important role in the development and immune escape of tumors. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression module. In combination with univariate Cox regression and analysis of least absolute shrinkage operator (LASSO), characteristics associated with CAFs were developed for a prognostic model. The migration and proliferation of lung cancer cells were evaluated in vitro. Finally, the expression levels of proteins were analyzed by Western blot. LASSO Cox regression algorithm was then performed to select hub genes. Finally, a total of 2 Genes (COL5A2, COL6A2) were obtained. We then divided LUAD patients into high- and low-risk groups based on CAFs risk scores. Survival analysis, CAFs score correlation analysis and tumor mutation load analysis showed that COL5A2 and COL6A2 were high-risk genes for LUAD. Human Protein Atlas (HPA), western blot and PCR results showed that COL5A2 and COL6A2 were up-regulated in LUAD tissues. When COL5A2 and COL6A2 were knocked down, the proliferation, invasion and migration of lung cancer cells were significantly decreased. Finally, COL5A2 can affect LUAD progression through the Wnt/ß-Catenin and TGF-ß signaling pathways. Our CAFs risk score model offers a new approach for predicting the prognosis of LUAD patients. Furthermore, the identification of high-risk genes COL5A2 and COL6A2 and drug sensitivity analysis can provide valuable candidate clues for clinical treatment of LUAD.

Novel Insights Into the International Association for the Study of Lung Cancer Grading System for Lung Adenocarcinoma.

The new grading system for lung adenocarcinoma proposed by the International Association for the Study of Lung Cancer (IASLC) defines prognostic subgroups on the basis of histologic patterns observed on surgical specimens. This study sought to provide novel insights into the IASLC grading system, with particular focus on recurrence-specific survival (RSS) and lung cancer-specific survival among patients with stage I adenocarcinoma. Under the IASLC grading system, tumors were classified as grade 1 (lepidic predominant with <20% high-grade patterns [micropapillary, solid, and complex glandular]), grade 2 (acinar or papillary predominant with <20% high-grade patterns), or grade 3 (≥20% high-grade patterns). Kaplan-Meier survival estimates, pathologic features, and genomic profiles were investigated for patients whose disease was reclassified into a higher grade under the IASLC grading system on the basis of the hypothesis that they would strongly resemble patients with predominant high-grade tumors. Overall, 423 (29%) of 1443 patients with grade 1 or 2 tumors classified based on the predominant pattern-based grading system had their tumors upgraded to grade 3 based on the IASLC grading system. The RSS curves for patients with upgraded tumors were significantly different from those for patients with grade 1 or 2 tumors (log-rank P < .001) but not from those for patients with predominant high-grade patterns (P = .3). Patients with upgraded tumors had a similar incidence of visceral pleural invasion and spread of tumor through air spaces as patients with predominant high-grade patterns. In multivariable models, the IASLC grading system remained significantly associated with RSS and lung cancer-specific survival after adjustment for aggressive pathologic features such as visceral pleural invasion and spread of tumor through air spaces. The IASLC grading system outperforms the predominant pattern-based grading system and appropriately reclassifies tumors into higher grades with worse prognosis, even after other pathologic features of aggressiveness are considered.

Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis.

AIMS: Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data. METHODS AND RESULTS: The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001). CONCLUSION: The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.

The Clinical Relevance of the Expression of SGLT2 in Lung Adenocarcinoma.

PURPOSE: We aimed to elucidate the functions and clinical relevance of sodium-glucose cotransporter 2 (SGLT2) in resected lung adenocarcinoma. METHODS: The protein expression of SGLT2 in tumor samples from 199 patients with lung adenocarcinoma was analyzed by immunohistochemistry, and the protein expression, clinical variables, and survival outcomes were compared. RESULTS: The median SGLT2 expression was significantly higher in advanced-stage and more aggressive adenocarcinomas. Age ≥70 (p < 0.01), BI ≥600 (p < 0.01), PRDX4 <25 (p < 0.01), and SGLT2 ≥12% (p = 0.03) were significant factors for RFS in multivariate analysis. Significant differences were observed in the RFS rates of the groups divided using the cutoff value of SGLT2 ≥12% (5-year RFS: 72.6% vs. 90%) (p < 0.01). CONCLUSION: The expression of SGLT2 was more frequently detected in advanced-stage and more aggressive adenocarcinomas with aggressive biological behavior than in their counterparts. The survival analysis revealed that the strong expression of SGLT2 was associated with poorer RFS. The SGLT2 expression predicts postoperative recurrence in lung adenocarcinoma patients.

Establishment and verification of novel TNM staging system for lung mucinous adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a high-mortality rate cancer. Within this category, Lung mucinous adenocarcinoma (LMAC) is a rare and distinct subtype of lung adenocarcinoma necessitating further investigation. The study was launched to compare the difference of survival features between LMAC and lung non-mucinous adenocarcinoma (LNMAC) and to investigate the significance and demand for developing a new staging system tailored to LMAC. METHODS: This retrospective study assessed the suitableness of the current staging system for LMAC. It compared the overall survival (OS) between LMAC and LNMAC from 2004 to 2020 (LNMAC: 160,387; LMAC: 6,341) and instituted a novel classification framework for LMAC based on US population. Verification group consisting of patients from two Chinese medical centers from 2010 to 2018 (n = 392) was set to ascertain the applicability of this novel system. The primary endpoint was OS. To minimize the bias, propensity score match (PSM) was employed. Survival analysis and Log-rank test were executed to explore the survival features of LMAC. RESULTS: The results indicated that the existed staging system was not suitable for LMAC. Patients diagnosed with LMAC exhibited a superior OS compared to those with LNMAC in stage IA2 (P < 0.0001), IA3 (P < 0.0001), IB (P = 0.0062), IIA (P = 0.0090), IIB (P = 0.0005). In contrast, a worse OS in stage IVA (P = 0.0103) was found in LMAC patients. The novel classification system proposed for LMAC proved to be highly applicable and demonstrated substantial efficacy, as confirmed by the verification group. CONCLUSION: The newly established classification system was more effective for LMAC, but it necessitates large-scale verification to confirm its applicability and reliability.

Multi­omics identification of a signature based on malignant cell-associated ligand-receptor genes for lung adenocarcinoma.

PURPOSE: Lung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches. METHODS: We constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts. RESULTS: We developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells. CONCLUSION: We have identified malignant cell-associated ligand-receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.

Optimal treatment strategies for hepatoid adenocarcinoma of the lung: insights from a comprehensive analysis.

BACKGROUND: Hepatoid adenocarcinoma of the lung (HAL) is a distinctly uncommon subtype of lung adenocarcinoma (LAC), characterized by hepatoid features and an alarmingly low 5-year survival rate of approximately 8%. The scarcity of information on this condition has contributed to the absence of standardized treatment protocols, and the molecular underpinnings of its pathogenesis remain largely unexplored. To bridge these gaps, this study compiled data from 191 primary HAL patients to delineate treatment patterns, prognostic factors, and potential pathogenic mechanisms. METHODS: This study was divided into two cohorts: cohort 1, comprising 110 patients extracted from the Surveillance, Epidemiology, and End Results (SEER) database, and cohort 2, consisting of 70 patients identified through a comprehensive literature review via the PubMed, Web of Science, and Scopus databases, in addition to 11 patients from Tongji Hospital. The Cox proportional hazards regression model was employed to identify independent prognostic factors. Kaplan-Meier survival curves were generated to assess the impact of treatment modalities centered around surgery and chemotherapy. Moreover, this study evaluated the efficacy of first-line treatment regimens and conducted Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses on identified mutated genes. RESULTS: The demographic and clinical profile of HAL patients typically comprises older individuals who are smokers, with a predisposition for diagnosis at advanced disease stages, culminating in a high mortality rate. Key prognostic indicators identified included disease stage, chemotherapy and surgical interventions. The study suggests a treatment strategy that advocates chemotherapy for patients with stage IV HAL and surgery for those with non-stage IV disease. The combination of paclitaxel and platinum-based chemotherapy emerged as an efficacious first-line treatment, with the integration of immunotherapy and targeted therapies showing potential benefits. Genetic analysis underscored similarities between HAL and LAC, particularly highlighting aberrant kinase activity (serine, threonine, and tyrosine) and the activation of PI3K-Akt and MAPK signaling pathways as contributing factors to HAL pathogenesis. CONCLUSION: Despite its relatively rare occurrence, this study underscores the significance of treatment strategies and concludes probable prognostic factors. Due to limited reports, a deeper understanding of the molecular mechanisms driving tumorigenesis and progression in HAL is needed.

Prognostic factors for resected invasive mucinous lung adenocarcinoma: a systematic review and meta-analysis.

BACKGROUND: Surgery is the optimal choice for early invasive mucinous lung adenocarcinoma (IMA). A systematic review and meta-analysis were conducted to explore the prognostic factors for resected IMA. METHODS: We systematically reviewed the prognostic role of clinicopathological and genomic factors in resected IMA patients. Eligible studies on the treatment of IMA following the systematic search of PubMed, Embase and the Cochrane Library from January 2015 to January 2024 were identified. Outcomes of interest were overall survival (OS) and disease-free survival/recurrence-free survival (DFS/RFS). The hazard ratio (HR) and 95% confidence interval (CI) were used as impact indicators for systematic review and meta-analysis. RESULTS: Sixteen studies involving 3,484 patients with IMA were included. The results of the combined analysis showed that male and smoking were associated with a worse prognosis. Furthermore, advanced clinical stage, poor differentiation grade, presence of visceral pleural invasion (VPI) and spread through air spaces (STAS), and presence of KRAS mutations were also associated with worse prognosis. CONCLUSIONS: Gender, smoking, clinical stage, tumor size, differentiation grading, VPI, STAS and KRAS mutation affect DFS/RFS and OS of IMA patients after surgery. Identifying these factors may aid physicians in developing more individualized treatment plans for resectable IMA patients.

eHSP90α in front-line therapy in EGFR exon 19 deletion and 21 Leu858Arg mutations in advanced lung adenocarcinoma.

PURPOSE: Extracellular heat shock protein 90 AA1(eHSP90α) is intricately linked to tumor progression and prognosis. This study aimed to investigate the difference in the value of eHSP90α in post-treatment response assessment and prognosis prediction between exon 19 deletion(19DEL) and exon 21 Leu858Arg(L858R) mutation types in lung adenocarcinoma(LUAD). METHODS: We analyzed the relationship between the expression of eHSP90α and clinicopathological features in 89 patients with L858R mutation and 196 patients with 19DEL mutation in LUAD. The Kaplan-Meier survival curve was used to determine their respective cut-off values and analyze the relationship between eHSP90α expression and the survival time of the two mutation types. The area under the curve (AUC) was used to evaluate the diagnostic performance of biomarkers. Then, the prognostic model was developed using the univariate-Cox multivariate-Cox and LASSO-multivariate logistic methods. RESULTS: In LUAD patients, eHSP90α was positively correlated with carcinoembryonic antigen(CEA), carbohydrate antigen 125(CA125), and carbohydrate antigen 153(CA153). The truncated values of eHSP90α in L858R and 19DEL patients were 44.5 ng/mL and 40.8 ng/mL, respectively. Among L858R patients, eHSP90α had the best diagnostic performance (AUC = 0.765), and higher eHSP90α and T helper cells(Th cells) expression were significantly related to shorter overall survival(OS) and worse treatment response. Also, high eHSP90a expression and short progression-free survival(PFS) were significantly correlated. Among 19DEL patients, CEA had the best diagnostic efficacy (AUC = 0.734), and CEA and Th cells were independent prognostic factors that predicted shorter OS. Furthermore, high CA125 was significantly associated with short PFS and poor curative effect. CONCLUSIONS: eHSP90α has a better prognostic value in LUAD L858R patients than 19DEL, which provides a new idea for clinical diagnosis and treatment.

In-depth exploration of the focus issues of TKI combined with radiotherapy for EGFR-mutant lung adenocarcinoma patients with brain metastasis: a systematic analysis based on literature metrology, meta-analysis, and real-world observational data.

BACKGROUND: There is a growing interest in utilizing a combination of brain radiotherapy (RT) and tyrosine kinase inhibitors (TKIs) for patients diagnosed with brain metastases (BM) in epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma (LAC). The current status of this treatment strategy remains a subject of debate. METHODS: We initiated our study by conducting a comprehensive literature search using the SCI-expanded database of Web of Science Core Collection (WoSCC). We utilized the VOSPviewer software to analyze various aspects of the research, including the year of publication, authorship, keywords, and country.Subsequently, we performed an extensive and systematic literature search on popular online databases. Our primary outcome measures were overall survival (OS) and intracranial progression-free survival (iPFS), both quantified by hazard ratios (HRs). Additionally, for data verification, we included data from patients in non-small cell lung cancer with brain metastasis who underwent therapeutic intervention at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the Radiotherapy Department of Hanzhong Central Hospital between August 2012 and November 2021. RESULTS: The bibliometric analysis revealed an increasing trend in research focused on the combination of RT and TKIs for the management of lung cancer brain metastases over the previous decade. Then, nine studies consistent with the research direction were included for meta-analysis. The meta-analysis showed that the OS (HR = 0.81, 95% confidence interval: 0.69-0.94; P = 0.007) and iPFS (HR = 0.71, 95% confidence interval: 0.61-0.82; P < 0.001) of the combination therapy were significantly prolonged. Finally, 168 EGFR-mutated BM advanced LAC patients in the real world were verified, and the median iPFS of the combination therapy (n = 88 and EGFR-TKIs alone (n = 80) were 16.0 and 9.0 months, respectively, (P < 0.001). The median OS was 29.0 and 27.0 months, respectively, with no dramatic difference (P = 0.188). CONCLUSIONS: Research on EGFR-mutant LAC brain metastasis has turned towards exploring optimal treatment strategies for this condition. Our meta-analysis and real-world data analysis consistently demonstrate that combination therapy offers a substantial improvement in patient survival compared to EGFR-TKI monotherapy. Notably, among patients undergoing salvage radiotherapy (RT), our subgroup analysis reveals that those initially treated with third-generation TKIs experience more significant benefits than those treated with first- or second-generation TKIs.

BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis.

In addition to considering the main effects, understanding gene-environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high-dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity-constrained accelerated failure time (BHAFT) models for identifying main and interaction (M-I) effects with novel spike-and-slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high-dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa-bayesian/BHAFT.

Differences in postoperative prognosis between early-stage lung adenocarcinoma and squamous cell carcinoma.

BACKGROUND: Although prognosis and treatments differ between small-cell- and nonsmall-cell carcinoma, comparisons of the histological types of NSCLC are uncommon. Thus, we investigated the oncological factors associated with the prognosis of early-stage adenocarcinoma and squamous cell carcinoma. METHODS: We retrospectively compared the clinicopathological backgrounds and postoperative outcomes of patients diagnosed with pathological stage I-IIA adenocarcinoma and squamous cell carcinoma primary lung cancer completely resected at our department from January 2007 to December 2017. Multivariable Cox regression analysis for overall survival and recurrence-free survival was performed. RESULTS: The median follow-up duration was 55.2 months. The cohort consisted of 532 adenocarcinoma and 96 squamous cell carcinoma patients. A significant difference in survival was observed between the two groups, with a 5-year overall survival rate of 90% (95% confidence interval 86-92%) for adenocarcinoma and 77% (95% CI 66-85%) for squamous cell carcinoma (P < 0.01) patients. Squamous cell carcinoma patients had worse outcomes compared to adenocarcinoma patients in stage IA disease, but there were no significant differences between the two groups in stage IB or IIA disease. In multivariate analysis, invasion diameter was associated with overall survival in adenocarcinoma (hazard ratio 1.76, 95% confidence interval 1.36-2.28), but there was no such association in squamous cell carcinoma (hazard ratio 0.73, 95% confidence interval 0.45-1.14). CONCLUSIONS: The importance of tumor invasion diameter in postoperative outcomes was different between adenocarcinoma and squamous cell carcinoma. Thus, it is important to consider that nonsmall-cell carcinoma may have different prognoses depending on the histological type, even for the same stage.

The impact of postoperative adjuvant therapy on EGFR-mutated stage IA lung adenocarcinoma with micropapillary pathological subtypes.

BACKGROUND: Micropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components. MATERIALS AND METHODS: We retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019. In terms of the proportion of MPP components (TPM), the tumors were reclassified into three categories: MPP patterns absent (TPMN); low proportions of MPP components (TPML); and high proportions of MPP components (TPMH). The dates of recurrence and metastasis were identified based on physical examinations and were confirmed by histopathological examination. RESULTS: Overall, 505 (TPMN, n = 375; TPML, n = 92; TPMH, n = 38) patients harboring EGFR mutations were enrolled in the study. Male sex (P = 0.044), high pathological stage (P < 0.001), and MPP pathological subtype (P < 0.001) were more frequent in the TPM-positive (TPMP) group than in the TPM-negative (TPMN) group. Five-year disease-free survival (DFS) rates were significantly lower in the TPMP group than in the TPMN group (84.5% vs. 93.4%, P = 0.006). In addition, patients with high proportions (greater than 10%) of MPP components had worse overall survival (OS) (91.0% vs. 98.9%, P = 0.025) than those with low proportions (5%≤ TPM ≤ 10%). However, postoperative EGFR tyrosine kinase inhibitors (TKIs) or adjuvant chemotherapy (ACT) cannot improve DFS and OS between EGFR-mutated patients with different proportions of MPP components. CONCLUSION: MPP was related to earlier recurrence and shortened survival time, even in stage IA. Further research needs a larger sample size to clarify that EGFR-mutated stage IA patients with MPP components obtain survival benefits from adjuvant therapy.

ACTL6A promotes repair of cisplatin-induced DNA damage, a new mechanism of platinum resistance in cancer.

Cisplatin is a mainstay of systemic therapy for a variety of cancers, such as lung cancer, head and neck cancer, and ovarian cancer. However, resistance to cisplatin represents one of the most significant barriers for patient outcome improvement. Actin-like 6A (ACTL6A) is a component of several chromatin remodeling complexes, including SWI/SNF, NuA4/TIP60 histone acetylase, and INO80. Amplification of ACTL6A gene is often seen in lung squamous cell carcinoma, ovarian cancer, and esophageal cancer, but its significance remains to be fully determined. Here we identify ACTL6A overexpression as a novel cause for platinum resistance. High levels of ACTL6A are associated with chemoresistance in several types of human cancer. We show that overexpression of ACTL6A leads to increased repair of cisplatin-DNA adducts and resistance to cisplatin treatment. In contrast, depletion of ACTL6A inhibits the repair of cisplatin-induced DNA lesions, and increases cisplatin sensitivity in cisplatin-resistant ovarian cancer cells. The regulation of repair by ACTL6A is mediated through the SWI/SNF chromatin remodeling complex. Treatment with a histone deacetylase inhibitor can reverse the effect of ACTL6A overexpression on the repair of cisplatin-induced DNA damage and render cancer cells more sensitive to cisplatin treatment in a xenograft mouse model. Taken together, our study uncovers a novel role for ACTL6A in platinum resistance, and provides evidence supporting the feasibility of using HDAC inhibitors for platinum resistant tumors.