Early-stage Lung Adenocarcinoma Research Articles

Spatial downregulation of CD74 signatures may drive invasive component development in part-solid lung adenocarcinoma

Pulmonary nodules with part-solid imaging features manifest during the progression from preinvasive to invasive lung adenocarcinoma. To define the spatial composition and evolutionary trajectories of early-stage lung adenocarcinoma, we combined spatial transcriptomics (ST) and pathological annotations from 20 part-solid nodules (PSNs), four of which were matched with single-cell RNA sequencing. Two malignant cell populations (MC1 and MC2) were identified, and a linear evolutionary relationship was observed. Compared to MC2, the pre-existing malignant MC1 exhibited a lower metastatic signature, corresponding to the preinvasive component (lepidic) on pathology and the ground glass component on PSN imaging. Higher immune infiltration was observed among MC1 regions in ST profiles, and further analysis revealed that macrophages may be involved in this process through the CD74 axis. This work provides deeper insights into the evolutionary process and spatial immune cell composition behind PSNs and highlights the mechanisms of immune escape behind this adenocarcinoma trajectory.

Prognosis of early-stage lung adenocarcinoma in young patients.

Lung adenocarcinoma (LUAD) is a familiar lung cancer with a poor prognosis. This study was meant to determine whether there are differences in survival between younger and older patients with early-stage LUAD because of the rise in the incidence of LUAD in young individuals over the previous few decades. We analysed the clinical, therapeutic and prognostic features of a cohort (2012-2013) of 831 consecutive patients with stage I/II LUAD who underwent curative surgical resection at Shanghai Pulmonary Hospital. Propensity score matching (PSM) was performed for age, sex, tumour size, tumour stage and therapy in a 2:1 ratio between the two groups without taking gender, illness stage at operation or decisive treatment into account. Following PSM analysis to create a 2:1 match for comparison, the final survival study included 163 patients with early-stage LUAD <50 years and 326 patients ≥50 years. Surprisingly, younger patients were overwhelmingly female (65.6%) and never smokers (85.9%). There were no statistical differences between the two groups in terms of the overall survival rate (P = 0.067) or time to advancement (P = 0.76). In conclusion, no significant differences stood out between older and younger patients with stage I/II LUAD regarding overall and disease-free survival rates. Younger patients with early-stage LUAD were more likely to be female and never smokers, which suggests that risk factors other than active smoking may be responsible for lung carcinogenesis in these patients.

An ensemble deep learning model for risk stratification of invasive lung adenocarcinoma using thin-slice CT

Lung cancer screening using computed tomography (CT) has increased the detection rate of small pulmonary nodules and early-stage lung adenocarcinoma. It would be clinically meaningful to accurate assessment of the nodule histology by CT scans with advanced deep learning algorithms. However, recent studies mainly focus on predicting benign and malignant nodules, lacking of model for the risk stratification of invasive adenocarcinoma. We propose an ensemble multi-view 3D convolutional neural network (EMV-3D-CNN) model to study the risk stratification of lung adenocarcinoma. We include 1075 lung nodules (≤30 mm and ≥4 mm) with preoperative thin-section CT scans and definite pathology confirmed by surgery. Our model achieves a state-of-art performance of 91.3% and 92.9% AUC for diagnosis of benign/malignant and pre-invasive/invasive nodules, respectively. Importantly, our model outperforms senior doctors in risk stratification of invasive adenocarcinoma with 77.6% accuracy [i.e., Grades 1, 2, 3]). It provides detailed predictive histological information for the surgical management of pulmonary nodules. Finally, for user-friendly access, the proposed model is implemented as a web-based system (https://seeyourlung.com.cn).

Immune microenvironment analysis and novel biomarkers of early-stage lung adenocarcinoma evolution.

Lung cancer is the deadliest and most diagnosed type of cancer worldwide. The 5-year survival rate of lung adenocarcinoma (LUAD) dropped significantly when tumor stages advanced. Patients who received surgically resecting at the pre-invasive stage had a 5-year survival rate of nearly 100%. However, the study on the differences in gene expression profiles and immune microenvironment among pre-invasive LUAD patients is still lacking. In this study, the gene expression profiles of three pre-invasive LUAD stages were compared using the RNA-sequencing data of 10 adenocarcinoma in situ (AIS) samples, 12 minimally invasive adenocarcinoma (MIA) samples, and 10 invasive adenocarcinoma (IAC) samples. The high expression levels of PTGFRN (Hazard Ratio [HR] = 1.45; 95% Confidence Interval [CI]: 1.08-1.94; log-rank P = 0.013) and SPP1 (HR = 1.44; 95% CI: 1.07-1.93; log-rank P = 0.015) were identified to be associated with LUAD prognosis. Moreover, the early LUAD invasion was accompanied by the enhancement of antigen presentation ability, reflected by the increase of myeloid dendritic cells infiltration rate (Cuzick test P < 0.01) and the upregulation of seven important genes participating in the antigen presentation, including HLA-A (Cuzick test P = 0.03), MICA (Cuzick test P = 0.01), MICB (Cuzick test P = 0.01), HLA-DPA1 (Cuzick test P = 0.04), HLA-DQA2 (Cuzick test P < 0.01), HLA-DQB1 (Cuzick test P = 0.03), and HLA-DQB2 (Cuzick test P < 0.01). However, the tumor-killing ability of the immune system was inhibited during this process, as there were no rising cytotoxic T cell activity (Cuzick test P = 0.20) and no increasing expression in genes encoding cytotoxic proteins. In all, our research elucidated the changes in the immune microenvironment during early-stage LUAD evolution and may provide a theoretical basis for developing novel early-stage lung cancer therapeutic targets.

B4GALT1 promotes immune escape by regulating the expression of PD-L1 at multiple levels in lung adenocarcinoma

BackgroundInvasive adenocarcinoma (IAC), which is typically preceded by minimally invasive adenocarcinoma (MIA), is the dominant pathological subtype of early-stage lung adenocarcinoma (LUAD). Identifying the molecular events underlying the progression from MIA to IAC may provide a crucial perspective and boost the exploration of novel strategies for early-stage LUAD diagnosis and treatment.MethodsTranscriptome sequencing of four pairs of MIA and IAC tumours obtained from four multiple primary lung cancer patients was performed to screen out beta-1,4-galactosyltransferase1 (B4GALT1). Function and mechanism experiments in vitro and in vivo were performed to explore the regulatory mechanism of B4GALT1-mediated immune evasion by regulating programmed cell death ligand 1 (PD-L1).ResultsB4GALT1, a key gene involved in N-glycan biosynthesis, was highly expressed in IAC samples. Further experiments revealed that B4GALT1 regulated LUAD cell proliferation and invasion both in vitro and in vivo and was related to the impaired antitumour capacity of CD8 + T cells. Mechanistically, B4GALT1 directly mediates the N-linked glycosylation of PD-L1 protein, thus preventing PD-L1 degradation at the posttranscriptional level. In addition, B4GALT1 stabilized the TAZ protein via glycosylation, which activated CD274 at the transcriptional level. These factors lead to lung cancer immune escape. Importantly, inhibition of B4GALT1 increased CD8 + T-cell abundance and activity and enhanced the antitumour immunity of anti-PD-1 therapy in vivo.ConclusionB4GALT1 is a critical molecule in the development of early-stage LUAD and may be a novel target for LUAD intervention and immunotherapy.

Glycoprofiling of early non-small cell lung cancer using lectin microarray technology

Abstract Objectives Non-small cell lung cancer (NSCLC) is one of the most common malignancies in the world with a high incidence and it lacks effective biomarkers for early-stage detection. In this investigation, we aimed to investigate the alterations in plasma glycans related to NSCLC and assess the possibility of plasma glycopatterns as potential biomarkers for the diagnosis of NSCLC. Methods First, plasma samples from 16 patients with early-stage lung adenocarcinoma (LUAD), 16 patients with early-stage Lung squamous cell carcinoma (LUSC), and 16 healthy volunteers, were selected for inclusion in this study to probe the difference in plasma glycopatterns using lectin microarrays. Then, the diagnostic effectiveness of the candidate lectins was evaluated using ROC. Results In contrast to the NL group, seven candidate lectins offered potential diagnostic utility in the NSCLC (LUAD and LUSC) group. F17AG was significantly altered in LUSC with an AUC of 0.818 (adj.P.Val&lt;0.05) compared to NL samples. There were 20 differentially expressed lectins in the LUAD group compared to the NL group. Based on the AUC values (AUC&gt;0.800) and the normalized fluorescence intensities of the lectins, we selected eight lectins, GAL2, PTL-1, GNA, SSA, LENTIL, CA, PHA-E, and MAA to perform logistic regression analysis, and found that the combination of these eight candidate lectins had high diagnostic potential. Conclusions The results of this study should help to distinguish between NSCLC and NL based on changes in plasma glycopatterns, which have a great deal of potential to be biomarkers for diagnosing NSCLC.

Nomograms for intraoperative prediction of lymph node metastasis in clinical stage IA lung adenocarcinoma.

Accurate prediction of lymph node metastasis (LNM) is critical for selecting optimal surgical procedures in early-stage lung adenocarcinoma (LUAD). This study aimed to develop nomograms for intraoperative prediction of LNM in clinical stage IA LUAD. A total of 1227 patients with clinical stage IA LUADs on computed tomography (CT) were enrolled to construct and validate nomograms for predicting LNM (LNM nomogram) and mediastinal LNM (LNM-N2 nomogram). Recurrence-free survival (RFS) and overall survival (OS) were compared between limited mediastinal lymphadenectomy (LML) and systematic mediastinal lymphadenectomy (SML) in the high- and low-risk groups for LNM-N2, respectively. Three variables were incorporated into the LNM nomogram and the LNM-N2 nomogram, including preoperative serum carcinoembryonic antigen (CEA) level, CT appearance, and tumor size. The LNM nomogram showed good discriminatory performance, with C-indexes of 0.879 (95% CI, 0.847-0.911) and 0.880 (95% CI, 0.834-0.926) in the development and validation cohorts, respectively. The C-indexes of the LNM-N2 nomogram were 0.812 (95% CI, 0.766-0.858) and 0.822 (95% CI, 0.762-0.882) in the development and validation cohorts, respectively. LML and SML had similar survival outcomes among patients with low risk of LNM-N2 (5-year RFS, 88.1% vs. 89.5%, Pp = 0.790; 5-year OS, 96.0% vs. 93.0%, p = 0.370). However, for patients with high risk of LNM-N2, LML was associated with worse survival (5-year RFS, 64.0% vs. 77.4%, p = 0.036; 5-year OS, 66.0% vs. 85.9%, p = 0.038). We developed and validated nomograms to predict LNM and LNM-N2 intraoperatively in patients with clinical stage IA LUAD on CT. These nomograms may help surgeons to select optimal surgical procedures.

A novel Chr1-miR-200 driven whole transcriptome signature shapes tumor immune microenvironment and predicts relapse in early-stage lung adenocarcinoma

BackgroundIn Lung adenocarcinoma (LUAD), targeted therapies and immunotherapies have moved from metastatic to early stage and stratification of the relapse risk becomes mandatory. Here we identified a miR-200 based RNA signature that delineates Epithelial-to-mesenchymal transition (EMT) heterogeneity and predicts survival beyond current classification systems.MethodsA miR-200 signature was identified using RNA sequencing. We scored the miR-200 signature by WISP (Weighted In Silico Pathology), used GSEA to identify pathway enrichments and MCP-counter to characterize immune cell infiltrates. We evaluate the clinical value of this signature in our series of LUAD and using TCGA and 7 published datasets.ResultsWe identified 3 clusters based on supervised classification: I is miR-200-sign-down and enriched in TP53 mutations IIA and IIB are miR-200-sign-up: IIA is enriched in EGFR (p < 0.001), IIB is enriched in KRAS mutation (p < 0.001). WISP stratified patients into miR-200-sign-down (n = 65) and miR-200-sign-up (n = 42). Several biological processes were enriched in MiR-200-sign-down tumors, focal adhesion, actin cytoskeleton, cytokine/receptor interaction, TP53 signaling and cell cycle pathways. Fibroblast, immune cell infiltration and PDL1 expression were also significantly higher suggesting immune exhaustion. This signature stratified patients into high-vs low-risk groups, miR-200-sign-up had higher DFS, median not reached at 60 vs 41 months and within subpopulations with stage I, IA, IB, or II. Results were validated on TCGA data on 7 public datasets.ConclusionThis EMT and miR-200-related prognostic signature refines prognosis evaluation independently of tumor stage and paves the way towards assessing the predictive value of this LUAD clustering to optimize perioperative treatment.

Metabolic profiles of lung adenocarcinoma via peripheral blood and diagnostic model construction

The metabolic profile of cancerous cells is shifted to meet the cellular demand required for proliferation and growth. Here we show the features of cancer metabolic profiles using peripheral blood of healthy control subjects (n = 78) and lung adenocarcinoma (LUAD) patients (n = 64). Among 121 detected metabolites, diagnosis of LUAD is based on arginine, lysophosphatidylcholine-acyl (Lyso.PC.a) C16:0, and PC-diacyl (PC.aa) C38:3. Network analysis revealed that network heterogeneity, diameter, and shortest path were decreased in LUAD. On the contrary, these parameters were increased in advanced-stage compared to early-stage LUAD. Clustering coefficient, network density, and average degree were increased in LUAD compared to the healthy control, whereas these topologic parameters were decreased in advanced-stage compared to early-stage LUAD. Public LUAD data verified that the genes encoding enzymes for arginine (NOS, ARG, AZIN) and for Lyso.PC and PC (CHK, PCYT, LPCAT) were related with overall survival. Further studies are required to verify these results with larger samples and other histologic types of lung cancer.

Combined measurement of circulating tumor cells and magnetic nanoparticles-assisted multiple blood markers improves the diagnostic efficiency of early-stage lung adenocarcinoma

The study aims to evaluate the efficiency and clinical value of circulating tumor cells (CTCs), blood tumor markers, and serum microRNAs for diagnosing lung adenocarcinoma in its early stages. The study included 40 patients with early-stage lung adenocarcinoma, 40 individuals with benign pulmonary nodules, and 40 healthy volunteers in groups 1, 2, and 3, respectively. The negative enrichment–fluorescence in situ hybridization was used to classify and quantify the aneuploidy and its number distribution in CTCs in groups 1–3. Magnetic nanoparticles were used to extract DNA. The levels of miR-223-3p and miR-486-5p in the serum of groups 1–3 were then determined using reverse transcription quantitative real-time polymerase chain reaction. CTC aneuploidy and its number distribution was detected and the detection of various blood markers was performed. The diagnostic accuracy was determined through receiver operating characteristic curve (ROC) drawn among the groups. The total number of CTCs and aneuploidies in patients with early-stage lung adenocarcinoma was higher than in patients with benign pulmonary nodules and healthy people. Patients with early-stage lung adenocarcinoma had significantly higher levels of miR-223-3p and miR-486-5p than patients with benign pulmonary nodules and healthy people. ROC analysis found that the sensitivity and area under the ROC curve of CTCs combined with multiple blood markers for distinguishing patients with early-stage lung adenocarcinoma from those without lung nodules were 80.12% and 0.945%, respectively. The sensitivity and area under the ROC curve of the patients were 85.38% and 0.948%, respectively. The detection of CTCs, carcinoembryonic antigen, cytokeratin 19 fragment, miR-223-3p, and miR-486-5p was effective for early-stage lung adenocarcinoma and benign lung nodules. The diagnosis of miR-223-3p is clinically significant, as the accurate diagnostic index of miR-223-3p is better than that of CTCs and other blood indicators. However, CTCs combined with blood markers have the highest efficiency in diagnosing early-stage lung adenocarcinoma.

Tumor-associated prognostic factors extractable from chest CT scans in patients with lung cancer.

Accurately predicting the prognosis of patients with lung cancer before or at the time of treatment would offer clinicians an opportunity to tailor management plans more precisely to individual patients. Considering that chest computed tomography (CT) scans are universally acquired in patients with lung cancer for clinical staging or response evaluation, fully extracting and utilizing the prognostic information embedded in this modality would be a reasonable approach. Herein, we review tumor-related prognostic factors that are extractable from CT scans, including the tumor dimensions, presence of ground-glass opacity (GGO), margin characteristics, tumor location, and deep learning-based features. Tumor dimensions include diameter and volume, which are among the most potent prognostic factors in lung cancer. In lung adenocarcinomas, the solid component size on CT scans as well as the total tumor size is associated with the prognosis. The areas of GGO indicate the lepidic component and are associated with better postoperative survival in early-stage lung adenocarcinomas. As for the margin characteristics, which represent the CT manifestation of fibrotic stroma or desmoplasia, tumor spiculation should be evaluated. The tumor location in the central lung is associated with occult nodal metastasis and is a worse prognostic factor per se. Last but not least, deep learning analysis enables prognostic feature extraction beyond the human eyes.

Comprehensive circulating microRNA profile as a supersensitive biomarker for early-stage lung cancer screening.

Less-invasive early diagnosis of lung cancer is essential for improving patient survival rates. The purpose of this study is to demonstrate that serum comprehensive miRNA profile is high sensitive biomarker to early-stage lung cancer in direct comparison to the conventional blood biomarker using next-generation sequencing (NGS) technology combined with automated machine learning (AutoML). We first evaluated the reproducibility of our measurement system using Pearson's correlation coefficients between samples derived from a single pooled RNA sample. To generate comprehensive miRNA profile, we performed NGS analysis of miRNAs in 262 serum samples. Among the discovery set (57 patients with lung cancer and 57 healthy controls), 1123 miRNA-based diagnostic models for lung cancer detection were constructed and screened using AutoML technology. The diagnostic faculty of the best performance model was evaluated by inspecting the validation samples (74 patients with lung cancer and 74 healthy controls). The Pearson's correlation coefficients between samples derived from the pooled RNA sample ≥ 0.98. In the validation analysis, the best model showed a high AUC score (0.98) and a high sensitivity for early stage lung cancer (85.7%, n = 28). Furthermore, in comparison to carcinoembryonic antigen (CEA), a conventional blood biomarker for adenocarcinoma, the miRNA-based model showed higher sensitivity for early-stage lung adenocarcinoma (CEA, 27.8%, n = 18; miRNA-based model, 77.8%, n = 18). The miRNA-based diagnostic model showed a high sensitivity for lung cancer, including early-stage disease. Our study provides the experimental evidence that serum comprehensive miRNA profile can be a highly sensitive blood biomarker for early-stage lung cancer.

Preoperative levels of folate receptor-positive circulating tumor cells in different subtypes of early-stage lung adenocarcinoma: Predictive value for determining extent of surgical resection.

The objective was to measure the correlations of preoperative levels of folate receptor-positive circulating tumor cells (FR+CTCs) with clinical characteristics and histologic subtype in early-stage lung adenocarcinoma, and to determine the predictive value of FR+CTC level in preoperative determination of the extent of surgical resection. In this retrospective, single-institution, observational study, preoperative FR+CTC levels were measured via ligand-targeted enzyme-linked polymerization in patients with early-stage lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was used to identify the optimal cutoff value of FR+CTC level for prediction of various clinical characteristics and histologic subtypes. No significant difference in FR+CTC level was observed among patients with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) (P = 0.813). Within the non-mucinous adenocarcinoma group, no difference was observed among patients with tumors whose predominant growth patterns were lepidic, acinar, papillary, micropapillary, solid, and complex gland (P = 0.053). However, significant differences in FR+CTC level were observed between patients with and without the micropapillary subtype [11.21 (8.22-13.61) vs. 9.85 (7.43-12.63), P = 0.017], between those with and without the solid subtype [12.16 (8.27-14.90) vs. 9.87 (7.50-12.49), P = 0.022], and between those with any of the advanced subtypes (micropapillary, solid, or complex glands) vs. none of these [10.48 (7.83-13.67) vs. 9.76 (7.42-12.42), P = 0.032]. FR+CTC level was also correlated with degree of differentiation of lung adenocarcinoma (P = 0.033), presence of visceral pleural invasion (VPI) of lung carcinoma (P = 0.003), and lymph node metastasis of lung carcinoma (P = 0.035). FR+CTC level is of potential predictive value in determining the presence of aggressive histologic patterns (micropapillary, solid, and advanced subtypes), degree of differentiation, and occurrence of VPI and lymph node metastasis in IAC. Measurement of FR+CTC level combined with intraoperative frozen sections may represent a more effective method of guiding resection strategy in cases of cT1N0M0 IAC with high-risk factors.

Abstract LB292: GCC2 on small extracellular vesicles for the early diagnosis of lung adenocarcinoma: A multicenter trial

Abstract Background: Early detection of lung cancer is extremely important for timely and effective therapeutic interventions to increase the survival rate of patients. Emerging evidence suggests that tumor-derived small extracellular vesicle (sEV) cargo may serve as cancer-specific biomarkers. We previously reported the identification of GRIP and coiled-coil domain-containing 2-enriched sEV (sEV-GCC2) as a promising biomarker for lung adenocarcinoma in a pilot study. In this multicenter study, we explored the diagnostic and therapeutic potential of sEV-GCC2 in early-stage lung adenocarcinoma. Methods: A total of 470 blood plasma samples (150 healthy controls and 320 patients with lung adenocarcinoma) were retrospectively obtained from five institutions. sEVs were isolated by size exclusion chromatography and sEV-GCC2 was quantified by enzyme-linked immunosorbent assay. Effect of sEV-GCC2 on lung cancer cell proliferation was investigated in vitro and in vivo. Results: sEV-GCC2 concentration was significantly higher in patients than that in controls with an area under the curve (AUC) of 0.856 (95% confidence interval [CI], 0.820-0.886). In patients at TisN0-T1miN0 stages vs controls, the AUC was 0.802 (95% CI, 0.734-0.859). The association between sEV-GCC2 and lung adenocarcinoma remained after adjustment for pathological TNM stage and tumor location in the left lower lobe. Immunohistochemical staining revealed that GCC2 expression was significantly higher in lung adenocarcinoma tissues than in the controls (p &amp;lt; 0.001). Furthermore, sEV-GCC2 enhanced cancer cell proliferation and accelerated tumor growth and lymph node metastasis. Conclusions: We identified sEV-GCC2 as a potential diagnostic marker for very early-stage lung cancer. sEV-GCC2 represents a promising therapeutic target for lung adenocarcinoma and may be quantified as key molecules in the progression of lung adenocarcinoma. Citation Format: Byeong Hyeon Choi, Hyonggin An, Sukki Cho, Sungsoo Lee, Hyeong Ryul Kim, Jong Ho Cho, Hyunku Shin, Ok Hwa Jeon, Yeonho Choi, Hyun Koo Kim. GCC2 on small extracellular vesicles for the early diagnosis of lung adenocarcinoma: A multicenter trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB292.

Molecular fingerprints of nuclear genome and mitochondrial genome for early diagnosis of lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer with high morbidity and mortality rates. Due to the heterogeneity of LUAD, its characteristics remain poorly understood. Exploring the clinical and molecular characteristics of LUAD is challenging but vital for early diagnosis.MethodsThis observational and validation study enrolled 80 patients and 13 healthy controls. Nuclear and mtDNA-captured sequencings were performed.ResultsThis study identified a spectrum of nuclear and mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with diagnosis. The correlation coefficient for somatic mutations in cfDNA and patient-matched tumor tissues was high in nuclear and mitochondrial genomes. The mutation number of highly mutated genes was evaluated, and the Least Absolute Shrinkage and Selection Operator (LASSO) established a diagnostic model. Receiver operating characteristic (ROC) curve analysis explored the diagnostic ability of the two panels. All models were verified in the testing cohort, and the mtDNA panel demonstrated excellent performance. This study identified somatic mutations in the nuclear and mitochondrial genomes, and detecting mutations in cfDNA displayed good diagnostic performance for early-stage LUAD. Moreover, detecting somatic mutations in the mitochondria may be a better tool for diagnosing early-stage LUAD.ConclusionsThis study identified specific and sensitive diagnostic biomarkers for early-stage LUAD by focusing on nuclear and mitochondrial genome mutations. This also further developed an early-stage LUAD-specific mutation gene panel for clinical utility. This study established a foundation for further investigation of LUAD molecular pathogenesis.

A prognostic and immunotherapeutic predictive model based on the cell-originated characterization of tumor microenvironment in lung adenocarcinoma

Tumor microenvironment (TME) plays a crucial role in predicting prognosis and response to therapy in lung cancer. Our study established a prognostic and immunotherapeutic predictive model, the tumor immune cell score (TICS), by differentiating cell origins in lung adenocarcinoma (LUAD) based on the transcriptomic data of 2,510 patients in 14 independent cohorts, including 12 public datasets and two in-house cohorts. The high TICS was associated with prolonged overall survival (OS), especially in the early-stage LUAD. For the advanced-stage LUAD, high TICS predicted a superior OS in patients who were treated with immunotherapy instead of chemotherapy or TKI. The result suggested that TICS could serve as an indicator for the prognostic stratification management of patients in the early-stage LUAD, and as a potential guide for therapeutic decision-marking in the advanced-stage LUAD. Our findings provided an insight into prognosis stratification and potential guidance for treatment strategy selection.

Abstract 3744: A circulating microRNA panel predicts recurrence and survival in early-stage lung adenocarcinoma

Abstract Background: Early-stage lung adenocarcinoma (LUAD) patients have substantial risk for recurrence and disease-related death. Cisplatin-based adjuvant chemotherapy remains the standard for care of LUAD patients who have undergone surgical resection with a high risk of recurrence. However, adjuvant chemotherapy is associated with increased risk of toxicity including chemotherapy-related death, with only a modest survival benefit. Therefore, there is an unmet need of biomarkers for assessment and identification of those in an early stage who would likely benefit from adjuvant chemotherapy. Circulating miRNAs are stably present in blood and potentially reflect different expressions in cancerous and non-cancerous tissues, making them attractive biomarkers. The purpose of this study was to identify circulating miRNAs useful for predicting recurrence in early-stage LUAD. Materials and Methods: miRNA microarray analysis was performed with pooled pretreatment plasma samples from stage I LUAD patients who developed recurrence within two years after curative surgery or remained recurrence free over a six-year follow-up period, as well as from healthy controls. miRNA biomarker candidates were assayed in two independent plasma sample sets from 85 stage I LUAD (validation set) and from 57 stage I and II LUAD (test set) patients. Results: Based on miRNA microarray data and previous reports, predictive performance of miR-23a-3p, miR-23b-3p, miR-191-5p, miR-185-5p, miR-151a-3p, miR-320c, miR-21-5p, miR-125b-5p, miR-30d-5p, and miR-197-3p was evaluated in the validation set. Plasma levels of miR-23a-3p, miR-185-5p, miR-320c, miR-21-5p, miR-125b-5p, miR-30d-5p, and miR-197-3p were significantly higher in those with recurrence as compared to those without. A miRNA panel comprised of miR-23a-3p, miR-320c, and miR-125b-5p was developed based on a logistic regression, with yielding an AUC of 0.776 (95% confidence interval [CI] = 0.660 to 0.893). The three-miRNA panel with fixed coefficients yielded an AUC of 0.804 (95% CI = 0.688 to 0.920) with a sensitivity of 45.8% at 95% specificity in the test set. The miRNA panel score was a significant and independent factor for predicting disease-free survival (DFS; P &amp;lt; 0.001, HR = 1.64, 95% CI = 1.51-4.22) and overall survival (OS; P = 0.001, HR = 1.51, 95% CI = 1.17-1.94). Conclusion: This circulating miRNA panel may serve as a noninvasive blood test for predicting DFS and OS in early-stage LUAD patients. Our findings provide rationale for further investigation to stratify early-stage LUAD patients using blood-based biomarkers to increase the ability to provide more personalized care. Citation Format: Mei-Chee Tai, Leonidas E. Bantis, Gargy Parhy, Taketo Kato, Ichidai Tanaka, Chi-Wan Chow, Junya Fujimoto, Carmen Behrens, Tetsunari Hase, Koji Kawaguchi, Johannes F. Fahrmann, Edwin Ostrin, Kohei Yokoi, Toyofumi F. Chen-Yoshikawa, Yoshinori Hasegawa, Samir M. Hanash, Ignacio I. Wistuba, Ayumu Taguchi. A circulating microRNA panel predicts recurrence and survival in early-stage lung adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3744.

Abstract 1415: The search for molecular biomarkers of relapse in early stage lung adenocarcinoma

Abstract Background: Recurrence cannot be completely prevented by resection or chemotherapy. Molecular biomarkers reported in previous studies have the potential to predict the recurrence risk of lung adenocarcinoma (LUAD), but the results were controversial. Methods: We retrospectively analyzed the molecular characteristics of the 218 early-stage patients with lung adenocarcinoma based on 599 gene-panel target sequencing. All the patients received no neoadjuvant therapy and no EGFR-TKI treatment. The follow-up information on recurrence was complete. Univariate and multivariate analyses were performed using the Cox proportional hazard models to investigate whether the common alterations in EGFR and KRAS were prognostic factors for relapse-free survival(RFS). Results: Among all the enrolled patients, the mutation rates of EGFR and KRAS were 47.6% and 9.3%, respectively. EGFR mutation was not proved to be a prognostics signature of relapse for lung adenocarcinoma regardless univariate and multivariate analysis (univariate: HR, 1.11; 95%CI, 0.82-1.50, P = 0.49; multivariate: HR, 1.18; 95%CI, 0.86-1.64, P = 0.31). The univariate and multivariate analysis identified KRAS alteration as an independent prognostic factor for a shorter RFS (univariate: HR, 1.64; 95%CI, 0.75-2.43, P &amp;lt; 0.05; multivariate: HR, 1.66; 95%CI, 1.19-2.32, P &amp;lt;0.05). For patients in pathological stage I, the patients with KRAS alterations showed significant recurrent risk compared with wild-type patients (HR, 2.02; 95%CI, 1.38-2.96; P &amp;lt;0.0.01). Conclusion: KRAS alterations rather than EGFR alterations were prognostic biomarkers of relapse for early-stage lung adenocarcinoma, especially for patients in pathological stage I. Citation Format: Honggang Ke, Zhongying Jing. The search for molecular biomarkers of relapse in early stage lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1415.

Abstract 4460: Spatial profiling of immune biomarkers in resected treatment-naïve early stage lung adenocarcinoma

Abstract Background: Recently, neoadjuvant immunotherapy plus chemotherapy has been approved for treatment of resectable non-small cell lung carcinoma (NSCLC). Defining the immune landscape of these tumors and its spatial distribution will help to understand lung cancer biology. Here, we analyzed the distribution of immune-related biomarkers in tumor-defined regions and its associations with clinicopathological variables in resected lung adenocarcinomas using high-plex profiling approaches. Methodology: Thirty-three FFPE tumor tissues from surgically resected treatment-naïve lung adenocarcinoma stage I/II were used to construct a tissue microarray from the MD Anderson ICON cohort. We used three 1-mm core per patient [2 from central tumor (CT), and 1 from invasive margin (IM)] and performed the GeoMx Digital Spatial Profiling protein protocol to assess 49 immune biomarkers. Pancytokeratin (panCK; epithelial), CD45 (immune) and SYTO 13 (nuclear) were utilized as morphology biomarkers. Regions of interests were placed in cores containing tumor, and segmented in ‘”Tumor (Tu)” (PanCK+) and the “tumor microenvironment (TME)” (PanCK-). Digital counts were normalized using background correction. Statistical analysis was performed using linear mixed model. A p value equal or less than 0.05 was considered significant. Results: We first compared the relative counts of immune biomarkers in the TME in CT and IM. IM had higher CD3, CD8, CD45RO, as well as CD163 and STING (P ranges 0.006 to 0.035), while CT had higher PD1 (P 0.025). Then we analyzed differential biomarker expression by sex and smoking status. Females had higher counts of Immune related biomarkers: CD45, CD3, CD20, immune checkpoints: PD-L1, VISTA, CTLA4, LAG3, and ICOS, and myeloid: CD68, CD11c, CD163, and B2M (P ranges 0.0005 to 0.046). Smokers had higher counts of CD66b (P 0.007) and B2M (P 0.039) while never smokers had higher counts of HLA-DR, CD34, FoxP3, OX40L, Tim-3, and B7-H3 (P ranges 0.001 to 0.049). Finally, we analyzed Tu segments. IM had higher CD66b, VISTA, CD163, OX40L, HLA-DR, GZMB, STING, and CD8 (P ranges 0.007 to 0.045) than CT. Female patients had higher CD45, CD68, CD11c and CD163 (P ranges 0.008 to 0.045), and males had higher SMA (P 0.005). Smokers had higher CD66b (P 0.007), B2-microglobulin (P 0.043), and never smokers had higher HLA-DR, STING, CD34, CD44, FoxP3 and CD25 (P ranges 0.006 to 0.043). Conclusions: In this study, biomarker analysis of treatment-naïve adenocarcinoma in CT areas and IM indicates a higher immune response in the IM and presence of inhibitory signaling inside the tumor. Our data also showed that tumors from females have higher immune response than tumors from males, which is concordant with previous studies. Distinct profiling by smoking status was also observed. Further analysis of gene expression analysis of this set is ongoing. Citation Format: Sharia D. Hernandez, Wei Lu, Alejandra G. Serrano, Claudio J. Arrechedera, Beatriz Sanchez-Espiridion, Nejla Ozirmak, Max Molina, Larisa Kostousov, Sean Barnes, Khaja Khan, Ximing Tang, Junya Fujimoto, Edwin R. Parra, Gabriela Raso, Stephanie T. Schmidt, Carmen Behrens, John Heymach, Jianjun Zhang, Ken Chen, Boris Sepesi, Tina Cascone, Don Gibbons, Ignacio I. Wistuba, Cara Haymaker, Luisa M. Solis. Spatial profiling of immune biomarkers in resected treatment-naïve early stage lung adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4460.

Abstract 3156: Meta-analysis of lung cancer single-cell RNA data reveals novel gene modules associated with lineage, stage, and genetic alterations

Abstract Objective: Combinations of somatic alterations, epigenetic changes, and interactions with cells in the tumor microenvironment can induce gene expression changes in cancer cells. Single-cell RNA-seq can provide valuable insights into the heterogeneity of cancer cells within and across tumor samples. We performed a meta-analysis of single-cell RNA-seq (scRNA-seq) datasets containing primary tumor samples from patients with non-small-cell-lung cancer (NSCLC) to characterize modules of co-expressed genes and determine associations with histological, genetic, and immune features. Methods: scRNA-seq data of 116,260 cells from 127 NSCLC samples including lung adenocarcinomas (LUADs) and lung squamous cell carcinomas (LUSCs) were collected and merged from 12 datasets. Cancer cells were identified by inferring copy number variations (CNVs). Celda was used to identify 163 gene co-expression modules across cancer cells. MAST was used to assess association of each module with histology, stage, and study. CaDrA was used to identify combinations of genomic features associated with gene modules projected into TCGA bulk RNA-seq. Result: Broad biological category of modules included those related to lineage, cell cycle and proliferation, extracellular matrix production (ECM), epithelial-to-mesenchymal transition (EMT), antigen presentation, xenobiotic metabolism, stress response, chemokine signaling, interferon signaling, housekeeping, and other general cellular processes. The modules most strongly associated with study-specific effects were enriched in housekeeping and ribosomal genes. Several ECM and cell-cycling modules were induced in advanced LUADs while MHC class II modules were reduced in late stage disease. Several modules containing different surfactant proteins or secretoglobins were identified and displayed heterogeneity within and across early-stage LUADs. Three modules in LUSCs were enriched for detoxification enzymes and associated with somatic mutations in different members of the Nrf2 pathway. A module of genes involved in keratinization displayed intra- and inter-tumoral heterogeneity across LUSCs and was associated with neutrophil infiltration scores in samples from TCGA. Conclusion: We employed a novel meta-analysis approach to study gene co-expression patterns that are active in lung cancer cells profiled with single-cell RNA-seq. Characterization of these modules revealed the biological processes and cancer hallmarks active within and across lung tumors. Citation Format: Rui Hong, Sarah Mazzilli, Stefano Monti, Avrum Spira, Joshua D. Campbell. Meta-analysis of lung cancer single-cell RNA data reveals novel gene modules associated with lineage, stage, and genetic alterations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3156.