Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Peritumoral and intratumoral radiomics for predicting visceral pleural invasion in lung adenocarcinoma based on preoperative computed tomography (CT)

AIM

To evaluate the prediction of peritumoral and intratumoral radiomics for visceral pleural invasion (VPI) in lung adenocarcinoma cancer (LAC) based on preoperative computed tomography (CT) radiomics.

MATERIALS AND METHODS

In total, 350 patients with LAC confirmed by surgery pathology were enrolled in The Second Hospital of Hebei Medical University, including 281 VPI negative patients and 69 VPI positive patients, were divided into the training cohort (n = 280) and validation cohort (n=70) at random with a ratio of 8:2. We extracted the radiomics features from the 3 region of interest (ROI), including gross tumor volume (GTV), the gross peritumoral tumor volume (GPTV) and the gross volume of the tumor rim (included the outer 4 mm of the tumor and 4mm of the tumor adjacent lung tissue on either side of the tumor contour boundary, GTR).The maximal redundancy minimal relevance (mMRM) algorithm and the least absolute shrinkage and selection operator (LASSO) was performed to reduce feature dimensionality and the radiomics score (Rad score) of the best radiomics model was combined with CT morphological characteristics with statistical significance in the univariable analysis to construct the combined model. The performance of the models was evaluated based on receiver operating characteristics (ROC) curve, calibration, and clinical usefulness. DeLong's test was used to assess differences in area under curve (AUC) between different models.

RESULTS

There were no statistically significant differences in patient's gender, age, and BMI between the VPI positive group and VPI negative group (all p＞0.05). There were statistically significant differences in the tumor maximum diameter, tumor CT image type, vacuole sign, and pleural indentation sign between the VPI positive group and VPI negative group (all p < 0.05). The models of radiomics of GTV, GPTV, and GTR showed high predictive value in the training cohort (All AUC > 0.75). Compared with GTV, GTR radiomics models, the GPTV radiomics model constructed via the logistic regression (LR) method exhibited better prediction performance with the AUCs of 0.819, 0.827; accuracy of 0.757,0.743; sensitivity of 0.800,0.786; specificity of 0.747,0.732 in the training and validation cohorts, respectively. The LR model of GPTV radiomics was defined as the optimal model for predicting VPI, since its excellent performance in both ROC, calibration curve and decision curve analysis (DCA).

CONCLUSION

Preoperative CT-based radiomics models can predict VPI in patients with LAC; the LR algorithm combined the GPTV radiomics was the optimal choice, demonstrating high sensitivity, specificity, accuracy and clinical usefulness.

Leveraging genome-wide association studies to better understand the etiology of cancers

Genome-wide association studies (GWAS) statistically assess the association between tens of millions of genetic variants in the whole genome and a phenotype of interest. Genome-wide association studies enable the elucidation of polygenic inheritance of cancer, in which myriad low-penetrance genetic variants collectively contribute to a substantial proportion of the heritable susceptibility. In addition to the robust genotype-phenotype associations provided by GWAS, combining GWAS data with functional genomic datasets or sophisticated statistical genetic methods unlocks deeper insights. Integrating genotype and molecular phenotyping data facilitates functional characterization of GWAS association signals through molecular quantitative trait loci mapping and transcriptome-wide association studies. Furthermore, aggregating genome-wide polygenic signals, including subthreshold associations, enables one to estimate genetic correlations across diverse phenotypes and helps in clinical risk predictions by evaluating polygenic risk scores. In this review, we begin by summarizing the rationale for GWAS of cancer, introduce recent methodological updates in the GWAS-derived downstream analyses, and demonstrate their applications to GWAS of cancers.

The causal nexus between diverse smoking statuses, potential therapeutic targets, and NSCLC: insights from Mendelian randomization and mediation analysis

Objective

Lung cancer, the most prevalent malignancy, is typically diagnosed at an advanced stage. Smoking is a pivotal risk factor for NSCLC, yet the impact of various smoking statuses on NSCLC remains unclear. Thus, this study aims to explore whether different smoking statuses can causally influence NSCLC through effects on predictive targets, offering a novel perspective for NSCLC treatment.

Methods

Employing dual-sample MR, MVMR, and TSMR approaches, we assessed the causal relationships between 13 distinct smoking statuses and NSCLC, using predicted potential therapeutic targets as mediators to further elucidate the causal interplay among them.

Results

Among the 13 smoking statuses, current tobacco smoking, exposure to tobacco smoke outside the home, past tobacco smoking, and never smoked demonstrated causal relationships with NSCLC. MVMR analysis reveals that Current tobacco smoking is an independent risk factor for NSCLC. Utilizing NCAPD2, IL11RA, and MLC1 as mediators, IL11RA (22.2%) was found to potentially mediate the relationship between past tobacco smoking and NSCLC.

Conclusion

This study, integrating bioinformatics and MR analysis, identified three potential predictive targets as mediators to investigate the causal relationships between different smoking statuses and NSCLC through potential therapeutic targets, providing new insights for the treatment and prevention of NSCLC.

Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.

Using a Polygenic Risk Score to Improve the Risk Prediction of Non-Small Cell Lung Cancer in Taiwan

PURPOSE

Low-dose computed tomography (LDCT) can help reducing lung cancer mortality. In Taiwan, the existing screening criteria revolve around smoking habits and family history of lung cancer. The role of genetic variation in non-small cell lung cancer (NSCLC) development is increasingly recognized. In this study, we aimed to investigate the potential benefits of polygenic risk scores (PRSs) in predicting NSCLC and enhancing the effectiveness of screening programs.

METHODS

We conducted a retrospective cohort study that included participants without prior diagnosis of lung cancer and later received LDCT for lung cancer screening. Genetic data for these participants were obtained from the project of Taiwan Precision Medicine Initiative. We adopted the model of genome-wide association study-derived PRS calculation using 19 susceptibility loci associated with the risk of NSCLC as reported by Dai et al.

RESULTS

We studied a total of 2,287 participants (1,197 male, 1,090 female). More female participants developed NSCLC during the follow-up period (4.4% v 2.5%, P = .015). The only risk factor of NSCLC diagnosis among male participants was age. Among female participants, independent risk factors of NSCLC diagnosis were age (adjusted hazard ratio [aHR], 1.08 [95% CI, 1.04 to 1.11]), a family history of lung cancer (aHR, 3.21 [95% CI, 1.78 to 5.77]), and PRS fourth quartile (aHR, 2.97 [95% CI, 1.25 to 7.07]). We used the receiver operating characteristics to show an AUC value of 0.741 for the conventional model. With the further incorporation of PRS, the AUC rose to 0.778.

CONCLUSION

The evaluation of PRS for NSCLC prediction holds promise for enhancing the effectiveness of lung cancer screening in Taiwan especially in women. By incorporating genetic information, screening criteria can be tailored to identify individuals at higher risks of NSCLC.

Semi-supervised lung adenocarcinoma histopathology image classification based on multi-teacher knowledge distillation

Objective.In this study, we propose a semi-supervised learning (SSL) scheme using a patch-based deep learning (DL) framework to tackle the challenge of high-precision classification of seven lung tumor growth patterns, despite having a small amount of labeled data in whole slide images (WSIs). This scheme aims to enhance generalization ability with limited data and reduce dependence on large amounts of labeled data. It effectively addresses the common challenge of high demand for labeled data in medical image analysis.Approach.To address these challenges, the study employs a SSL approach enhanced by a dynamic confidence threshold mechanism. This mechanism adjusts based on the quantity and quality of pseudo labels generated. This dynamic thresholding mechanism helps avoid the imbalance of pseudo-label categories and the low number of pseudo-labels that may result from a higher fixed threshold. Furthermore, the research introduces a multi-teacher knowledge distillation (MTKD) technique. This technique adaptively weights predictions from multiple teacher models to transfer reliable knowledge and safeguard student models from low-quality teacher predictions.Main results.The framework underwent rigorous training and evaluation using a dataset of 150 WSIs, each representing one of the seven growth patterns. The experimental results demonstrate that the framework is highly accurate in classifying lung tumor growth patterns in histopathology images. Notably, the performance of the framework is comparable to that of fully supervised models and human pathologists. In addition, the framework's evaluation metrics on a publicly available dataset are higher than those of previous studies, indicating good generalizability.Significance.This research demonstrates that a SSL approach can achieve results comparable to fully supervised models and expert pathologists, thus opening new possibilities for efficient and cost-effective medical images analysis. The implementation of dynamic confidence thresholding and MTKD techniques represents a significant advancement in applying DL to complex medical image analysis tasks. This advancement could lead to faster and more accurate diagnoses, ultimately improving patient outcomes and fostering the overall progress of healthcare technology.

Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

Polygenic inheritance and its interplay with smoking history in predicting lung cancer diagnosis: a French-Canadian case-control cohort

BACKGROUND

The most near-term clinical application of genome-wide association studies in lung cancer is a polygenic risk score (PRS).

METHODS

A case-control dataset was generated consisting of 4002 lung cancer cases from the LORD project and 20,010 ethnically matched controls from CARTaGENE. A genome-wide PRS including >1.1 million genetic variants was derived and validated in UK Biobank (n = 5419 lung cancer cases). The predictive ability and diagnostic discrimination performance of the PRS was tested in LORD/CARTaGENE and benchmarked against previous PRSs from the literature. Stratified analyses were performed by smoking status and genetic risk groups defined as low (<20th percentile), intermediate (20-80th percentile) and high (>80th percentile) PRS.

FINDINGS

The phenotypic variance explained and the effect size of the genome-wide PRS numerically outperformed previous PRSs. Individuals with high genetic risk had a 2-fold odds of lung cancer compared to low genetic risk. The PRS was an independent predictor of lung cancer beyond conventional clinical risk factors, but its diagnostic discrimination performance was incremental in an integrated risk model. Smoking increased the odds of lung cancer by 7.7-fold in low genetic risk and by 11.3-fold in high genetic risk. Smoking with high genetic risk was associated with a 17-fold increase in the odds of lung cancer compared to individuals who never smoked and with low genetic risk.

INTERPRETATION

Individuals at low genetic risk are not protected against the smoking-related risk of lung cancer. The joint multiplicative effect of PRS and smoking increases the odds of lung cancer by nearly 20-fold.

FUNDING

This work was supported by the CQDM and the IUCPQ Foundation owing to a generous donation from Mr. Normand Lord.

High-throughput characterization of functional variants highlights heterogeneity and polygenicity underlying lung cancer susceptibility

Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility.

Identification of pathogenic germline variants in a large Chinese lung cancer cohort by clinical sequencing

Genetic factors play significant roles in the tumorigenicity of lung cancer; however, there is lack of systematic and large-scale characterization of pathogenic germline variants for lung cancer. In this study, germline variants in 146 preselected cancer-susceptibility genes were detected in 17 904 Chinese lung cancer patients by clinical next-generation sequencing. Among 17 904 patients, 1738 patients (9.7%) carried 1840 pathogenic/likely pathogenic (P/LP) variants from 87 cancer-susceptibility genes. SBDS (SBDS ribosome maturation factor) (1.37%), TSHR (thyroid stimulating hormone receptor) (1.20%), BLM (BLM RecQ like helicase) (0.62%), BRCA2 (BRCA2 DNA repair associated) (0.62%), and ATM (ATM serine/threonine kinase) (0.45%) were the top five genes with the highest overall prevalence. The top mutated pathways were all involved in DNA damage repair (DDR). Case-control analysis showed SBDS c.184A>T(p.K62*), TSHR c.1574T>C(p.F525S), BRIP1 (BRCA1 interacting helicase 1) c.1018C>T(p.L340F), and MUTYH (mutY DNA glycosylase) c.55C>T(p.R19*) were significantly associated with increased lung cancer risk (q value < 0.05). P/LP variants in certain genes were associated with early onset of lung cancer. Our study indicates that Chinese lung cancer patients have a higher prevalence of P/LP variants than previously reported. P/LP variants are distributed in multiple pathways and dominated by DNA damage repair-associated pathways. The association between identified P/LP variants and lung cancer risk requires further studies for verification.

Acidic Environment-Responsive Metal Organic Framework-Mediated Dihydroartemisinin Delivery for Triggering Production of Reactive Oxygen Species in Drug-Resistant Lung Cancer

Background

Dihydroartemisinin (DHA) has emerged as a promising candidate for anticancer therapy. However, the application of DHA in clinics has been hampered by several limitations including poor bioavailability, short circulation life, and low solubility, significantly restricting its therapeutic efficacy and leading to notable side effects during the treatment.

Purpose

We present DHA-loaded zeolitic imidazolate framework-8 (D-ZIF) with controllable and targeted DHA release properties, leading to enhanced antitumor effects while reducing potential side effects.

Methods

D-ZIF was prepared by one-pot synthesis method using methylimidazole (MIM), Zn(NO3)2•6H2O and DHA. We characterized the physical and chemical properties of D-ZIF by TEM, DLS, XRD, FT-IR, and TG. We measured the drug loading efficiency and the cumulative release of DHA in different pH conditions. We evaluated the cytotoxicity of D-ZIF on renal cell carcinoma (RCC786-O), glioma cells (U251), TAX-resistant human lung adenocarcinoma (A549-TAX) cells by CCK8 in vitro. We explored the possible antitumor mechanism of D-ZIF by Western blot. We evaluated the biocompatibility and hemolysis of D-ZIF and explored the in vivo antitumor efficiency in mice model by TUNEL testing and blood biomarker evaluations.

Results

D-ZIF showed rhombic dodecahedral morphology with size of 129±7.2 nm and possessed a noticeable DHA encapsulation efficiency (72.9%). After 48 hours, D-ZIF released a cumulative 70.0% of the loaded DHA at pH 6.5, and only 42.1% at pH 7.4. The pH-triggered programmed release behavior of D-ZIF could enhance anticancer effect of DHA while minimizing side effects under normal physiological conditions. Compared with the free DHA group with 31.75% of A549-TAX cell apoptosis, the percentage of apoptotic cells was approximately 76.67% in the D-ZIF group. D-ZIF inhibited tumor growth by inducing tumor cell apoptosis through the mechanism of ROS production and regulation of Nrf2/HO-1 and P38 MAPK signaling pathways. D-ZIF showed potent effects in treating tumors with high safety in vivo.

Conclusion

This pH-responsive release mechanism enhanced the targeting efficiency of DHA towards tumor cells, thereby increasing drug concentration in tumor sites with negligible side effects. Herein, D-ZIF holds great promise for curing cancers with minimal adverse effects.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies.

METHODS

This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications.

RESULTS

We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets.

CONCLUSIONS

Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

Interaction between Continuous Pack-Years Smoked and Polygenic Risk Score on Lung Cancer Risk: Prospective Results from the Framingham Heart Study

BACKGROUND

Lung cancer risk attributable to smoking is dose dependent, yet few studies examining a polygenic risk score (PRS) by smoking interaction have included comprehensive lifetime pack-years smoked.

METHODS

We analyzed data from participants of European ancestry in the Framingham Heart Study Original (n = 454) and Offspring (n = 2,470) cohorts enrolled in 1954 and 1971, respectively, and followed through 2018. We built a PRS for lung cancer using participant genotyping data and genome-wide association study summary statistics from a recent study in the OncoArray Consortium. We used Cox proportional hazards regression models to assess risk and the interaction between pack-years smoked and genetic risk for lung cancer adjusting for European ancestry, age, sex, and education.

RESULTS

We observed a significant submultiplicative interaction between pack-years and PRS on lung cancer risk (P = 0.09). Thus, the relative risk associated with each additional 10 pack-years smoked decreased with increasing genetic risk (HR = 1.56 at one SD below mean PRS, HR = 1.48 at mean PRS, and HR = 1.40 at one SD above mean PRS). Similarly, lung cancer risk per SD increase in the PRS was highest among those who had never smoked (HR = 1.55) and decreased with heavier smoking (HR = 1.32 at 30 pack-years).

CONCLUSIONS

These results suggest the presence of a submultiplicative interaction between pack-years and genetics on lung cancer risk, consistent with recent findings. Both smoking and genetics were significantly associated with lung cancer risk.

IMPACT

These results underscore the contributions of genetics and smoking on lung cancer risk and highlight the negative impact of continued smoking regardless of genetic risk.

NEAT1_1 confers gefitinib resistance in lung adenocarcinoma through promoting AKR1C1-mediated ferroptosis defence

Gefitinib is one of the most extensively utilized epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) for treating advanced lung adenocarcinoma (LUAD) patients harboring EGFR mutation. However, the emergence of drug resistance significantly compromised the clinical efficacy of EGFR-TKIs. Gaining further insights into the molecular mechanisms underlying gefitinib resistance holds promise for developing novel strategies to overcome the resistance and improve the prognosis in LUAD patients. Here, we identified that the inhibitory efficacy of gefitinib on EGFR-mutated LUAD cells was partially dependent on the induction of ferroptosis, and ferroptosis protection resulted in gefitinib resistance. Among the ferroptosis suppressors, aldo-keto reductase family 1 member C1 (AKR1C1) exhibited significant upregulation in gefitinib-resistant strains of LUAD cells and predicted poor progression-free survival (PFS) and overall survival (OS) of LUAD patients who received first-generation EGFR-TKI treatment. Knockdown of AKR1C1 partially reversed drug resistance by re-sensitizing the LUAD cells to gefitinib-mediated ferroptosis. The decreased expression of miR-338-3p contributed to the aberrant upregulation of AKR1C1 in gefitinib-resistant LUAD cells. Furthermore, upregulated long non-coding RNA (lncRNA) nuclear paraspeckle assembly transcript 1_1 (NEAT1_1) sponged miR-338-3p to neutralize its suppression on AKR1C1. Dual-luciferase reporter assay and miRNA rescue experiment confirmed the NEAT1_1/miR-338-3p/AKR1C1 axis in EGFR-mutated LUAD cells. Gain- and loss-of-function assays demonstrated that the NEAT1_1/miR-338-3p/AKR1C1 axis promoted gefitinib resistance, proliferation, migration, and invasion in LUAD cells. This study reveals the effects of NEAT1_1/miR-338-3p/AKR1C1 axis-mediated ferroptosis defence in gefitinib resistance in LUAD. Thus, targeting NEAT1_1/miR-338-3p/AKR1C1 axis might be a novel strategy for overcoming gefitinib resistance in LUAD harboring EGFR mutation.

Lung cancer in patients who have never smoked - an emerging disease

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

A novel telomere biology disease-associated gastritis identified through a whole exome sequencing-driven approach

A whole exome sequencing (WES)-driven approach to uncover the etiology of unexplained inflammatory gastritides has been underutilized by surgical pathologists. Here, we discovered the pathobiology of an unusual chronic atrophic gastritis in two unrelated patients using this approach. The gastric biopsies were notable for an unusual pattern of gastritis with persistent dense inflammation, loss of both parietal and neuroendocrine cells in the oxyntic mucosa, and sparing of the antral mucosa. The patients were found to harbor pathogenic variants in telomeropathic genes (POT1 and DCLRE1B). Clonality testing for one of the patients showed evidence of evolving clonality of TCR-gene rearrangement. Both patients showed significantly decreased numbers of stem/progenitor cells by immunohistochemistry, which appears to be responsible for the development of mucosal atrophy. No such cases of unusual chronic atrophic gastritis in the setting of telomeropathy have been previously reported. The loss of stem/progenitor cells suggests that stem/progenitor cell exhaustion in the setting of telomere dysfunction is the likely mechanism for development of this unusual chronic atrophic gastritis. The results underscore the need for close monitoring of these gastric lesions, with special regard to their neoplastic potential. This combined WES-driven approach has promise to identify the cause and mechanism of other uncharacterized gastrointestinal inflammatory disorders.

Polygenic Risk Score, Environmental Tobacco Smoke, and Risk of Lung Adenocarcinoma in Never-Smoking Women in Taiwan

Importance

Estimating absolute risk of lung cancer for never-smoking individuals is important to inform lung cancer screening programs.

Objectives

To integrate data on environmental tobacco smoke (ETS), a known lung cancer risk factor, with a polygenic risk score (PRS) that captures overall genetic susceptibility, to estimate the absolute risk of lung adenocarcinoma (LUAD) among never-smokers in Taiwan.

Design, Setting, and Participants

The analyses were conducted in never-smoking women in the Taiwan Genetic Epidemiology Study of Lung Adenocarcinoma, a case-control study. Participants were recruited between September 17, 2002, and March 30, 2011. Data analysis was performed from January 17 to July 15, 2022.

Exposures

A PRS was derived using 25 genetic variants that achieved genome-wide significance (P < 5 × 10-8) in a recent genome-wide association study, and ETS was defined as never exposed, exposed at home or at work, and exposed at home and at work.

Main Outcomes and Measures

The Individualized Coherent Absolute Risk Estimator software was used to estimate the lifetime absolute risk of LUAD in never-smoking women aged 40 years over a projected 40-year span among the controls by using the relative risk estimates for the PRS and ETS exposures, as well as age-specific lung cancer incidence rates for never-smokers in Taiwan. Likelihood ratio tests were conducted to assess an additive interaction between the PRS and ETS exposure.

Results

Data were obtained on 1024 women with LUAD (mean [SD] age, 59.6 [11.4] years, 47.9% ever exposed to ETS at home, and 19.5% ever exposed to ETS at work) and 1024 controls (mean [SD] age, 58.9 [11.0] years, 37.0% ever exposed to ETS at home, and 14.3% ever exposed to ETS at work). The overall average lifetime 40-year absolute risk of LUAD estimated using PRS alone was 2.5% (range, 0.6%-10.3%) among women never exposed to ETS. When integrating both ETS and PRS data, the estimated absolute risk was 3.7% (range, 0.6%-14.5%) for women exposed to ETS at home or work and 5.3% (range, 1.2%-12.1%) for women exposed to ETS at home and work. A super-additive interaction between ETS and the PRS (P = 6.5 × 10-4 for interaction) was identified.

Conclusions and Relevance

This study found differences in absolute risk of LUAD attributed to genetic susceptibility according to levels of ETS exposure in never-smoking women. Future studies are warranted to integrate these findings in expanded risk models for LUAD.

Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants

BACKGROUND

Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer.

METHODS

We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer.

RESULTS

Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses.

CONCLUSION

Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.

Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.

New insights into the biology and development of lung cancer in never smokers-implications for early detection and treatment

Lung cancer is the leading cause of cancer deaths worldwide. Despite never smokers comprising between 10 and 25% of all cases, lung cancer in never smokers (LCNS) is relatively under characterized from an etiological and biological perspective. The application of multi-omics techniques on large patient cohorts has significantly advanced the current understanding of LCNS tumor biology. By synthesizing the findings of multi-omics studies on LCNS from a clinical perspective, we can directly translate knowledge regarding tumor biology into implications for patient care. Primarily focused on never smokers with lung adenocarcinoma, this review details the predominance of driver mutations, particularly in East Asian patients, as well as the frequency and importance of germline variants in LCNS. The mutational patterns present in LCNS tumors are thoroughly explored, highlighting the high abundance of the APOBEC signature. Moreover, this review recognizes the spectrum of immune profiles present in LCNS tumors and posits how it can be translated to treatment selection. The recurring and novel insights from multi-omics studies on LCNS tumor biology have a wide range of clinical implications. Risk factors such as exposure to outdoor air pollution, second hand smoke, and potentially diet have a genomic imprint in LCNS at varying degrees, and although they do not encompass all LCNS cases, they can be leveraged to stratify risk. Germline variants similarly contribute to a notable proportion of LCNS, which warrants detailed documentation of family history of lung cancer among never smokers and demonstrates value in developing testing for pathogenic variants in never smokers for early detection in the future. Molecular driver subtypes and specific co-mutations and mutational signatures have prognostic value in LCNS and can guide treatment selection. LCNS tumors with no known driver alterations tend to be stem-like and genes contributing to this state may serve as potential therapeutic targets. Overall, the comprehensive findings of multi-omics studies exert a wide influence on clinical management and future research directions in the realm of LCNS.

Immunogenetic polymorphisms predict therapeutic efficacy and survival outcomes in tumor patients receiving PD-1/PD-L1 blockade

BACKGROUND

While immune checkpoint inhibitors (ICIs) demonstrate remarkable clinical responses, only a small subset of patients obtains benefits. Genes linked to the tumor immune system are confirmed to be critical for the treatment of ICIs, and their polymorphisms can contribute to ICI efficacy. Here, we examined the potential of immunogenetic variations to predict the efficacy and survival of the PD-1/PD-L1 blockade.

METHODS

Cancerous patients receiving PD-1/PD-L1 blockade were recruited and followed up. Pivotal genes related to tumor-immunity were filtered through a protein-protein interaction network and the degree algorithm in Cytoscape. Finally, 39 genetic variants were genotyped through multiplex genotyping assays. Association analyses between variants and ICI efficacy and progression-free survival (PFS) were performed.

RESULTS

Overall, 318 patients were ultimately enrolled. Hence, three immunogenetic variants were identified as predictors of PD-1/PD-L1 blockade response. Mutant alleles from ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911 were all at increased risk of tumor progression following ICI therapy (OR: 1.475, 1.641, 1.462, respectively; P value: 0.028, 0.017, 0.027, respectively). Significant immunogenetic variants also attained similar trends in the PD-1 blockade, lung cancer, or lung cancer using PD-1 blockade subgroups. Furthermore, the mutant genotypes of CD274 rs2297136 (GG as the reference: HR: 0.50 (95%CI: 0.29-0.88), P value: 0.015) and TLR4 rs1927911 (AA as the reference: HR: 0.65 (95%CI: 0.47-0.91), P value: 0.012) indicated poorer PFS and were both independent prognostic factors.

CONCLUSION

Immunogenetic polymorphisms, including ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911, were first identified as potential predictors of response to PD-1/PD-L1 blockade in tumor patients.