Early-stage Lung Squamous Cell Carcinoma Research Articles

A novel gene signature related to fatty acid metabolism predicts prognosis, immune landscape, and drug sensitivity in early-stage lung squamous cell carcinoma.

Dysregulation of fatty acid metabolism (FAM) represents a significant metabolic alteration in tumorigenesis. However, the role of FAM-related genes (FAMRGs) in early-stage lung squamous cell carcinoma (LUSC) remains incompletely understood. A series of bioinformatic analyses and machine learning strategies were performed to construct a FAMRGs-based signature to predict prognosis and guide personalized treatment for early-stage LUSC patients. FAMRGs were screened through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the Molecular Signature Database (MSigDB). Prognosis FAMRGs were identified using univariate Cox regression, and unsupervised clustering analysis facilitated the division of the cohort into different clusters. The least absolute shrinkage and selection operator (LASSO)-Cox regression and multivariate regression analysis were employed to develop a FAMRGs-based signature for predicting overall survival (OS). A nomogram was subsequently constructed to facilitate risk assessment for individual patients. Comprehensive analyses of metabolic pathways, immune infiltration, immunomodulators, and potentially applicable drugs were conducted across different FAMRGs-related risk groups. The FAMRGs-based signature, comprising nine genes (ACOT11, APOH, BMX, CYP2R1, DPEP3, FABP6, FADS2, GLYATL2, and THRSP), demonstrated robust predictive capabilities for prognosis in The Cancer Genome Atlas (TCGA)-LUSC dataset and validated across six independent Gene Expression Omnibus (GEO)-LUSC datasets. Notably, the FAMRGs-base signature exhibited superior prognostic capacity and accurate survival prediction compared to conventional clinicopathological features. Furthermore, the signature was closely associated with immune cell infiltration, human leukocyte antigen (HLA) genes, and immune checkpoint genes expression. Additionally, the signature demonstrated potential sensitivity to chemo-/target-therapy. The FAMRGs-based signature demonstrated superior sensitivity in predicting the prognosis of early-stage LUSC. Detecting FAMRGs may provide predictive targets for the development of clinical treatment strategies.

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<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>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.

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma.

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC). From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression. Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue. Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

Segmentectomy for clinically early-stage primary squamous cell carcinoma of the lung.

Squamous cell carcinoma of the lung-the second most common subtype of lung cancer-has a poorer prognosis than lung adenocarcinoma. However, in contrast to lobectomy, the oncological outcomes after segmentectomy for primary squamous cell carcinomas remain unknown; hence, this study investigated these outcomes. Patients who underwent lobectomy or segmentectomy for clinically node-negative primary lung squamous cell carcinoma with a whole tumor size of ≤ 30 mm on preoperative computed tomography scan during April 2010 to December 2020 were included in this study. The cumulative incidence of recurrence (CIR) among all included patients and propensity score-matched patients were compared using the Gray method. Multivariate analysis using propensity scores and surgical procedures was performed using the Fine and Gray method. Overall, 230 patients were included in this study; of these, 172 (74.8%) underwent lobectomy and 58 (25.2%) underwent segmentectomy. No significant differences were observed in the CIR between patients who underwent lobectomy and those who underwent segmentectomy (5-year rate 18.1% vs. 14.2%; p = 0.787). Moreover, no significant differences in CIR were observed between the propensity score-matched patients who underwent lobectomy (n=43) and those who underwent segmentectomy (n = 43) (8.6% vs. 8.0%; p=0.571). Multivariable analysis was performed for CIR using the propensity score; it revealed that segmentectomy was not a significant predictor of worse CIR (hazard ratio, 0.987; p= 0.980). Segmentectomy may be feasible for treating clinically early-stage lung squamous cell carcinoma; its oncological outcomes are similar to those of lobectomy.

A novel pyroptosis-related lncRNA prognostic signature associated with the immune microenvironment in lung squamous cell carcinoma

BackgroundA growing body of evidence suggests that pyroptosis-related lncRNAs (PRncRNAs) are associated with the prognoses of tumor patients and their tumor immune microenvironments. However, the function of PRlncRNAs in lung squamous cell carcinoma (LUSC) remains unclear.MethodsWe downloaded the transcriptome and clinical information of 551 LUSC samples from the The Cancer Genome Atlas (TCGA) database and randomly separated patients with complete information into two cohorts. Based on the training cohort, we developed a pyroptosis-related signature. We then examined the signature in the test cohort and all retained patients. We also clustered two risk groups in each cohort according to the signature and performed survival analysis, functional analysis, tumor immune microenvironment analysis and drug sensitivity analysis.ResultsA prognostic signature containing five PRlncRNAs (AP001189.1, PICART1, LINC02555, AC010422.4, and AL606469.1) was developed. A principal component analysis (PCA) indicated better differentiation between patients with different risk scores. Kaplan–Meier (K–M) analysis demonstrated poorer survival among patients with higher risk scores (P < 0.001). A receiver operating characteristic (ROC) curve analysis provided evidence confirming the accuracy of the signature, and univariate (p = 0.005) and multivariate (p = 0.008) Cox regression analyses confirmed the independent value of the risk score in prognoses. Clinical subgroup validation indicated that the signature was more suitable for patients with early-stage LUSC. We also created a nomogram to increase the accuracy of the prediction. Moreover, functional analysis revealed that pathways related to tumor development and pyroptosis were enriched in the high-risk group. Furthermore, the prognostic signature was proven to be a predictor of sensitivity to immunotherapy and chemotherapy.ConclusionsWe developed a novel pyroptosis-associated signature with independent value for the prognosis of LUSC patients. PRlncRNAs are closely associated with the tumor immune microenvironment in LUSC and might offer new directions for immunotherapy.

Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma.

BackgroundEarly-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets.MethodsGene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm.ResultsA signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group.ConclusionA signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.

Phase I Trial of Dose-Escalated Five-Fraction Stereotactic Ablative Radiotherapy for Early-Stage Lung Squamous Cell Carcinoma

We aimed to evaluate the safety of and maximum tolerated dose (MTD) for 5-fraction stereotactic ablative radiotherapy (SABR) for early-stage lung squamous cell carcinoma (SCC), for which local failure rates appears higher than that of early-stage adenocarcinomas.A single institution phase I study was conducted in pathologically confirmed early-stage lung SCC. The 3+3 design involved 4 dose levels of 11, 12, 13, and 14 Gy x 5 fractions delivered every other day (dose levels DL1, DL2, DL3, and DL4, respectively). The primary objective was to determine the MTD of 5-fraction SABR, which was defined as the dose associated with a 33% rate of dose-limiting toxicities, defined as grade ≥3 respiratory/mediastinal or cardiac events (or grade ≥4 gastrointestinal or chest wall events), with toxicities reported until data lock in October 2020. Target volume delineation and organ-at-risk (OAR) constraints were based on RTOG 0813, using OAR constraints expressed in percent of prescription as fixed constraints from the 11 Gy per fraction prescription for all DL. Institutional constraints for the chest wall were used (V30 < 30cm3, up to 70 cm3 acceptable; maximum point dose 52.5 Gy). Target coverage objectives included ≥95% of the planning target volume (PTV) to be covered by 100% of the prescription dose, and 100% of the internal target volume (ITV) to receive ≥110% of the prescription dose. For technically challenging cases, it was permitted to prescribe as low as 50 Gy (BED of 100 Gy10) to a small portion of the GTV, ITV (if used) and corresponding PTV adjacent to a critical OAR (split target volume prescription). SABR was delivered using free breathing, deep inspiration breathhold, or expiratory gating. Thus, ITVs were not used for all patients.From October 2017 to June 2020, 13 patients were enrolled: 3 in DL1, 3 in DL2, 4 in DL3, and 3 in DL4. Seven (IASLC definition) or 6 (RTOG) patients had central lesions, and the rest abutted the chest wall. All patients completed SABR per protocol without major deviations. At 18.4 months median follow-up (range, 2.4-25.6 months), no patient developed dose limiting toxicities. There were no grade 4-5 events and 1 grade 3 event (painful brachial plexopathy, which occurred in DL1 at 16 months post-SABR at the time of local progression). There were 7 instances of grade 2 toxicities. These included fatigue (n = 1, DL2), chest wall pain (n = 2, DL2 & DL4), cough (n = 1, DL3), dyspnea (n = 2, DL3 & DL4), nausea (n = 1, DL4), and wheezing (n = 1, DL4). Eight (62%) patients required utilization of "split target volume" prescriptions. The mean total dose to the GTV ranged from 60.9-62.2 Gy for DL1, 63.2-68.6 Gy for DL2, 67.3-78.8 Gy for DL3, and 75.5-82.2 Gy for DL4. The median GTV was 19.9 cc (range 5-57cc).5-fraction SABR for early-stage lung SCC up to 14 Gy x 5 fractions using a split target prescription for OAR adjacent tumor appears safe. Long term follow up will be needed to assess late toxicities and tumor control. (NCT03321747).

A Novel Pyroptosis-Related Gene Signature for Early-Stage Lung Squamous Cell Carcinoma.

BackgroundDiagnosis of early stage lung squamous cell carcinoma (LUSC) has improved; however, a comprehensive analysis of prognostic signatures is needed.PurposeTo identify, establish, and validate a signature model based on pyroptosis-related genes for prognostic predictions of early stage LUSC.Patients and MethodsTwo independent cohorts were included. RNA-seq transcriptome data from patients with early stage LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Thirty-three pyroptosis-related genes were analyzed between early stage LUSC and normal lung tissues. Cox regression analysis, random survival forest, and least absolute shrinkage and selection operator algorithms established a three-gene signature. Kaplan–Meier survival and receiver-operating characteristic curves assessed the prognostic efficacy of the model. Single-sample gene set enrichment analysis (ssGSEA) assessed the relationship between pyroptosis and immune cells. Patients with early stage LUSC from the GSE74777 dataset were used for validation. Pyroptosis-related genes were verified by RT-qPCR and Western blotting.ResultsTwenty-three differentially expressed pyroptosis-related genes were identified in the LUSC and adjacent normal tissues. Three differentially expressed pyroptosis-related genes were identified as hub genes in early stage LUSC. Patients with early stage LUSC in the TCGA cohort were classified into low- and high-risk subgroups according to the risk score. Overall survival (OS) was significantly short in the high-risk subgroup versus the low-risk subgroup. A similar result was found for the GSE74777 dataset. ssGSEA of immune cells and immune-related pathways between the low- and high-risk subgroups may explain the different OS for patients with early-stage LUSC. IL-6 expression was upregulated, which was inconsistent with the bioinformatic analysis. NOD1 and CASP4 were downregulated in LUSC (all P < 0.05) versus normal lung tissues.ConclusionDifferentially expressed pyroptosis-related genes may be involved in early stage LUSC. Pyroptosis-related genes are important in tumor immunity and may be potential prognostic predictors for early stage LUSC.

TP53 and CDKN2A mutations in patients with early-stage lung squamous cell carcinoma: an analysis of the correlations and prognostic outcomes.

BackgroundLung squamous cell carcinoma (LUSC) is characterized by frequent mutations of tumor protein p53 (TP53) and cyclin dependent kinase inhibitor 2A (CDKN2A). However, to date, the impact of TP53/CDKN2A status on the clinical outcome of patients with early-stage LUSC is unclear.MethodsTissue samples from 16 early-stage, surgically resected LUSCs were analyzed by next-generation sequencing (NGS). Information regarding TP53 and CDKN2A alterations and patient survival time was downloaded from The Cancer Genome Atlas (TCGA) database. The associations between TP53 and CDKN2A status and tumor characteristics, outcomes including overall survival (OS) and disease-free survival (DFS), and mutation counts were investigated.ResultsTP53 and CDKN2A exhibited a high frequency of somatic mutations in early-stage LUSC in our center. Data for 1,176 samples were collected from TCGA. CDKN2A mutation status was associated with TP53 mutation status (P=0.040). TP53 mutation was a favorable prognostic factor for early-stage LUSC. The OS times of patients with wild-type and mutated TP53 were 28.94 and 60.48 months, respectively (P=0.002). In contrast, CDKN2A mutations were significantly associated with a shorter survival time in early-stage LUSC. The OS times for wild-type and mutated CDKN2A patients were 62.81 and 37.55 months, respectively (P=0.026). Patients with TP53 mutations had higher total mutation counts compared to patients with wild-type TP53. Furthermore, OS was significantly shorter in patients with a low mutation count compared to patients with a median or high mutation count.ConclusionsEarly-stage LUSC patients with TP53 mutations had a longer OS, while those with CDKN2A mutations had a shorter OS. Furthermore, patients with TP53 mutation/CDKN2A wild-type status had a longer OS. CDKN2A mutation is a vital indicator for prognostic assessment according to TP53 status. The prolonged survival of patients with TP53 mutations may be due to their high mutation counts. Larger datasets are required to validate these observations.

The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied

Simple SummaryThe most commonly diagnosed lung cancer is non-small-cell lung cancer (NSCLC). In contrast, the most frequent subtypes of NSCLC, accounting for 80% of cases, are ADC and SCC. Nevertheless, subtype identification is based on the diagnosis of characteristic gene mutations occurring in each subtype. The aim of the study was the metabolomics analysis of the early stage of NSCLC and the determination of new biochemical pathways differentiating the subtypes. Our studies demonstrated that there are new potential significant changes in the biochemical pathways involved in N-acylethanolamine (NAE) biosynthesis that distinguish early-stage SCC from ADC. Moreover, the analysis of the plasma of patients with COPD and NSCLC allows the exclusion of metabolites related to inflammation in the lungs and the identification of compounds characteristic of cancer. Our research indicates new pathways that have not been explored in NSCLC so far, which may have diagnostic, prognostic, and therapeutic potential.Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.

Risk assessment model and nomogram established by differentially expressed lncRNAs for early-stage lung squamous cell carcinoma.

BackgroundThe aim of this paper is to identify the differentially expressed lncRNAs (DELs) that could serve as markers for the prognosis of early-stage (stage I–II) lung squamous cell carcinoma (SCC).MethodslncRNAs expression data and corresponding clinical information for 395 patients with stage I–II lung SCC were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and LASSO regression were used to screen key lncRNAs, which were then were subjected to a multivariate Cox regression analysis. Furthermore, based on the results of multivariate analysis, lncRNAs with statistical significance were utilized to establish a risk assessment model. Also, a prognostic nomogram based on the risk assessment model was built. These two tools were evaluated by receiver operating characteristic (ROC) curve. Additionally, Kaplan-Meier (KM) survival curves for potential prognostic lncRNAs and clinical factors were performed.ResultsA total of 5 key lncRNAs (AC015712.4, LINC02301, AGAP11, AC099850.3, and AC008915.1) were screened to construct the risk assessment model, and the area under the ROC curves (AUC) showed the model had a general performance. The risk level of the model was identified as an independent prognostic factor for stage I–II lung SCC. A nomogram combining the lncRNA-based risk assessment model, age, and T stage was constructed to predict 3- and 5-year overall survival (OS) in patients with stage I–II lung SCC. The results of ROC and calibration curves demonstrated that the nomogram was reliable in predicting OS rate. Besides, KM survival curves showed OS time was significantly corrected with the expression of AC015712.4, age, and T stage.ConclusionsIn the present study, a risk assessment model and a nomogram based on five lncRNAs were constructed to predict OS time for early-stage lung SCC, which may contribute to the management of lung SCC.

A23 A Genomically Adjusted Clinicopathologic Model Predicts Recurrence in Resected Early-Stage Lung Squamous Cell Carcinoma

In contrast to lung adenocarcinoma, identification of clinically relevant genomic perturbations in lung squamous cell carcinoma (LUSC) remains poorly characterized. Prognostic and therapeutic decisions following surgery in early and locoregionally advanced LUSC are almost exclusively driven by the TNM classification system, omitting high-risk clinicopathologic and tumor genomic information. To address this knowledge gap, we sought to determine if a combined clinicopathologic and genomic model could predict disease-free survival (DFS) better than traditional TNM assessments in completely resected LUSC. A retrospective cohort study of a prospectively maintained database was performed for patients (N=95) with pathologic stage I-III LUSC who underwent complete resection from 2008-2018. Patients who received any induction therapy (N=9) were excluded. All patients had complete clinicopathologic data with broad-panel next-generation sequencing of the primary tumor, including matched controls to bioinformatically filter germline variants. DFS, the primary endpoint, and overall survival (OS) were estimated using Kaplan-Meier. Genomic pathway alterations (N=10) were determined as we previously reported. The prognostic model established associations between high-risk clinicopathologic variables and genomic alterations with DFS through Cox regression models. Concordance probability estimate (CPE) was used to discriminate performance between the existing TNM model and the developed prediction models. The median age was 70 years (range, 55-84), one-third were female (n=35), 55% (N=52) were pathologic stage I, and 98% (N=93) were ever-smokers. Median follow-up was 2 years. Recurrence occurred in 20% (19/95) and DFS was 74% (95% CI, 84-96%) at two years. Clinicopathologic features associated with DFS were lymphovascular invasion, visceral-pleural invasion, and pathologic stage. Tumor genomic analysis revealed alterations in the transcription factor BCL6 were independently associated with worse DFS (HR 5.23, 95% CI 1.73, 15.9, p=0.009), while mutations in the tumor suppressor ARID1A were associated with a worse OS (HR 2.98, 95% CI 0.91, 9.77, p=0.07). Pathway-centric analyses revealed no associations with our primary or secondary endpoints. Our prognostic clinicopathologic model outperformed the internally validated TNM model (CPE, 0.74 vs. 0.70) for prediction of DFS and our clinicopathologic model, adjusted for BCL6 genomic alterations, further improved discrimination (CPE=0.77). We show that integration of high-risk clinicopathologic and tumor genomic profiling better predicts DFS than TNM classification alone in early-stage, surgically resected LUSC – an observation that may facilitate enrichment in future adjuvant therapy clinical trials. This exploratory genomic analysis also suggests future studies investigate putative therapeutic vulnerabilities in LUSC tumors harboring BCL6 and ARD1A genomic alterations.

Characterization of microRNAs and lncRNAs in early-stage squamous cell carcinoma based on the analysis of TCGA datasets

Lung squamous cell carcinoma (LUSC) is highly malignant with poor prognosis, causing prevalent mortality worldwide. Early-stage lung cancer can be distinguished through reliable early detection to urge timely treatment. Non-coding RNAs (ncRNAs) might play such a vital role in tumor initiation, progression and metastasis that they are becoming an important biomarker in cancer screening. To identify the relation between ncRNAs and the early-stage of LUSC, we analyzed the data from the Cancer Genome Atlas (TCGA) database. We identified 28 microRNAs (miRNAs) and 32 long non-coding RNA (lncRNA) that were specifically expressed in early-stage LUSC, and the relationship was shown by the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. The result derived from Kaplan–Meier survival curves analysis showed that two miRNAs (hsa-miR-22-3p and hsa-miR-552-3p) and a lncRNA (FLJ36000) were negatively correlated with overall survival, but two miRNAs (hsa-miR-27b-5p and hsa-miR-340-5p) and five lncRNAs (CHK8-CPT1B, LINC00167, S NHG15, TTC28-AS1 and WASH7P) were positively associated. Our study provides novel insight for better understanding of early-stage LUSC and facilitates the identification of potential biomarkers for diagnosis and prognosis of early-stage LUSC.

Genomic landscape and its correlations with tumor mutational burden, PD-L1 expression, and immune cells infiltration in Chinese lung squamous cell carcinoma

IntroductionTo depict the genomic landscape of Chinese early-stage lung squamous cell carcinoma (LUSC) and investigate its correlation with tumor mutation burden (TMB), PD-L1 expression, and immune infiltrates.MethodsWhole-exome sequencing was performed on 189 surgically resected LUSC. TMB was defined as the sum of nonsynonymous single nucleotide and indel variants. CD8+ tumor-infiltrating lymphocyte (TIL) density and PD-L1 expression were evaluated by immunohistochemistry. Six immune infiltrates were estimated using an online database.ResultsThe median TMB was 9.43 mutations per megabase. Positive PD-L1 expression and CD8+ TILs density were identified in 24.3% and 78.8%. PIK3CA amplification was associated with significantly higher TMB (P = 0.036). Frequent genetic alterations had no impact on PD-L1 expression but PIK3CA amplification and KEAP1 mutation were independently associated with significantly lower CD8+ TIL density (P < 0.001, P = 0.005, respectively). Low TMB and high CD8+ TIL density were independently associated with longer disease-free survival (DFS) while none of them could individually predict the overall survival (OS). Combination of TMB and PD-L1 expression or TMB and CD8+ TIL density could stratify total populations into two groups with distinct prognosis. Classifying tumor-immune microenvironment based on PD-L1 expression and CD8+ TIL density showed discrepant genomic alterations but similar TMB, clinical features, and OS. Notably, patients with different smoking status had distinct prognostic factors.ConclusionThe combination of TMB, PD-L1 expression, immune infiltrates, and smoking status showed the feasibility to subgroup stratification in Chinese patients with early-stage LUSC, which might be helpful for future design of personalized immunotherapy trials in LUSC.

Abstract 4550: Correlations between tumor mutation burden, inflammatory profile and histological characteristics of tumor microenvironment in early-stage squamous cell lung carcinoma

Abstract Background: Anti-PD1/PD-L1 immunotherapy has demonstrated success in the treatment of advanced non-small cell lung cancer (NSCLC). Clinical data have shown that both the expression of PD-L1 in patient tumors and high tumor mutation burden (TMB) predicts the likelihood of a positive response to anti-PD-1/PD-L1 immunotherapy. Also, tumor microenvironment (TME) is the constitutive element in cancer immunity, in which analysis of characteristics reflects the potential existing immune reaction. Method: Histologic sections from 150 squamous cell lung carcinoma (SqCLC) were evaluated by two pathologists independently for percentage and character of intratumoral inflammatory cells and percentage and character of para-tumoral infiltrate. The ratios of infiltrating inflammatory cells to tumor cells were estimated in 10% increments by microscopic inspection. The proportions of immune cell populations were deconvulated using the CIBERSORT method based on Affymetrix gene expression profiles. PD-L1 protein expression by IHC was evaluated using the Dako PD-L1 22C3 pharmDx kit and scoring was determined according to the Dako tumor proportion score (TPS). Tumor Mutation Burden (TMB) was calculated based on data from targeted genome sequencing. CD4 and CD8 mRNA levels were determined from Affymetrix gene expression data from frozen specimens. Results: The infiltrates could be divided into intratumoral and paratumoral patterns according to their location in relation to microscopic tumor cell nests. Using the CIBERSORT assay, we confirmed our histological findings by microscopic examination that the SqCLC cohort can be subtyped into plasma cell dominant (74.8%) or other immune infiltrates dominant (such as macrophages), based on the proportions of immune cell populations. We found by regression analysis that TMB had a negative correlation with the percentage of intratumoral inflammatory cells (P=0.014), but did not significantly correlate with paratumoral infiltrates. The TMB demonstrated a significant negative correlation with CD4 mRNA level (P=0.017), but not with CD8 mRNA level. No correlation was determined for TMB and the immune cells dominant subgroup. Interestingly, we didn’t find any association for PD-L1 protein expression with the percentage of intra- or para-tumoral infiltrates, plasma cells dominant group and CD4 and CD8 mRNA levels. Conclusions: TMB was negatively correlated with the percentage of intratumoral inflammatory cells and CD4 mRNA level, which indicate that high TMB may promote an immune suppression environment. In addition, we did not find any association of PD-L1 expression with characteristics of TME in this early-stage SqCLC cohort. Further studies are needed to verify these interesting results. Citation Format: Hui Yu, Daniel T. Merrick, Ming-Sound Tsao, William G. Richards, Lucian R. Chirieac, Mark A. Watson, Christopher J. Rivard, David H. Harpole, Raphael Bueno, Adrie van Bokhoven, Aik-Choon Tan, Fred R. Hirsch, Wilbur A. Franklin. Correlations between tumor mutation burden, inflammatory profile and histological characteristics of tumor microenvironment in early-stage squamous cell lung carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4550.

P2.09-11 TMB Estimated with Targeted NGS in Early Stage Squamous Cell Carcinoma: Correlation with PD-L1 Expression and Lymphocyte Density

It has been proposed that a combination of assays may refine the prediction of response to checkpoint inhibitors, with tumour mutation burden (TMB) being lately the strongest biomarker associated with efficacy. Although some targeted next generation sequencing (NGS) assays provide a good estimate of whole exome sequencing TMB, they are only available throughout referral laboratories. We sought to investigate the possibility of profiling TMB in-house with a commercially available targeted NGS assay, and to correlate the results with survival, the status of TP53, PD-L1 overexpression and tumor-infiltrating lymphocytes (TILs). The study included samples from 40 patients diagnosed with early-stage lung squamous cell carcinoma. PD-L1 immunohistochemistry (IHC) was performed with two clones (SP263 and SP142, Ventana Medical Systems). CD8+ TILs were scored with a digital algorithm. The status of TP53 (exons 4–10) was investigated with direct sequencing. Ion TorrentTM OncomineTM Tumor Mutation Load Assay (ThermoFisher Scientific), a targeted NGS assay which covers 1.7Mb across 409 cancer driver genes, was used to assess TMB. NGS was performed on genomic DNA from FFPE tumor samples using the Ion S5TM system. The results were analyzed with the Ion ReporterTM software. According to the manufacturer’s instructions, TMB was calculated based on the number of non-synonymous somatic mutations, after removing polymorphisms and known or predicted driver mutations from all the variants. We investigated the correlation between TMB and PD-L1 expression, lymphocyte density, TP53 status and survival. TMB data was available for all 40 patients. The mean and median number of mutations was 13 and 11, respectively. CD8+/mm2 TILs within the peritumoral stromal compartment ranged from 312 to 4793 and within the intraepithelial compartment ranged from 17 to 2002. Sixty percent and 32% of cases were positive in tumor cells with SP263 or SP142, respectively (1% cut-off). Immune cells PD-L1 expression (1% cut-off) was observed in 92% of samples with both clones. No correlation was found between PD-L1 expression or lymphocyte density and TMB. Tumors with TP53 mutations showed non-significant higher numbers of mutations than those wild-type (p=0.075). Accordingly, there was a similar trend for overall survival using the median number of mutations as a cut-off (p=0.137, HR, 5.29). It is feasible to use targeted NGS to estimate TMB. In our pilot study, there was no obvious correlation with other immunooncology predictive biomarkers. Funding: AES 2017/Feder. ISCIII: PI17/01001

Correlation of PD-L1 Expression with Tumor Mutation Burden and Gene Signatures for Prognosis in Early-Stage Squamous Cell Lung Carcinoma

ObjectivesAnti–programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) immunotherapy has demonstrated success in the treatment of advanced NSCLC. Recently, PD-1/PD-L1 blockade also has demonstrated interesting results in small trials of neoadjuvant treatment in stage IB to IIIA NSCLC. In addition, several clinical trials using anti–PD-1/PD-L1 immunotherapy as an adjuvant or neoadjuvant treatment in patients with resectable stage NSCLC are ongoing. However, few analyses of anti–PD-1/PD-L1 immunotherapy–related biomarkers in early-stage squamous cell lung carcinoma (SqCLC) have been reported. In this study, we evaluated PD-L1 protein expression, tumor mutation burden, and expression of an immune gene signature in early-stage SqCLC, providing data for identifying the potential role for patients with anti–PD-1/PD-L1 treatment in early-stage SqCLC. MethodsA total of 255 specimens from patients with early-stage SqCLC were identified within participating centers of the Strategic Partnering to Evaluate Cancer Signatures program. PD-L1 protein expression by immunohistochemistry was evaluated by using the Dako PD-L1 22C3 pharmDx kit on the Dako Link 48 auto-stainer (Dako, Carpinteria, CA). Tumor mutation burden (TMB) was calculated on the basis of data from targeted genome sequencing. The T-effector and interferon gamma (IFN-γ) gene signature was determined from Affymetrix gene chip data (Affymetrix, Santa Clara, CA) from frozen specimens. ResultsThe prevalence of PD-L1 expression was 9.8% at a tumor proportion score cutoff of at least 50%. PD-L1 mRNA and programmed cell death 1 ligand 2 mRNA positively correlated with PD-L1 protein expression on tumor cells (TCs) and tumor-infiltrating immune cells. PD-L1 protein expression on tumor-infiltrating immune cells was correlated with the T-effector and IFN-γ gene signature (p < 0.001), but not with TMB. For TCs, all of these biomarkers were independent of each other and neither PD-L1 protein expression, TMB, or T-effector and IFN-γ gene signatures were independently prognostic for patient outcomes. ConclusionsEvaluation of PD-L1 expression, TMB, and T-effector and IFN-γ gene signatures in the cohort with early-stage SqCLC found them to be independent of each other, and none was associated with overall survival. Our results also support the hypothesis that PD-L1 expression is regulated by an intrinsic mechanism on TCs and an adaptive mechanism on immune cells.

Identification of a progression-associated long non-coding RNA signature for predicting the prognosis of lung squamous cell carcinoma.

Long non-coding RNAs (lncRNAs) have been indicated to have prognostic roles in various cancer types. However, the association between lncRNAs and lung squamous cell carcinoma (LSCC) progression, and the prognostic value of lncRNAs as a marker for early detection of LSCC have not been systematically investigated. The present study performed a genome-wide comparative analysis in order to determine the expression profiles of 10,207 lncRNAs to investigate the expression patterns between patients with early stages of LSCC (stage I–II) and those with late-stage disease (stage III–IV). It was found that 114 lncRNAs were significantly differentially expressed between late- and early-stage LSCC and therefore associated with the progression of the malignancy. By focusing on progression-associated lncRNAs, eight lncRNAs were found to be significantly associated with overall survival of LSCC patients according to univariate Cox proportional hazards regression analysis. These eight prognostic lncRNAs were integrated into a progression-associated eight-lncRNA signature, which stratified patients into two groups with significantly different overall survival (median survival, 2.25 vs. 7.68 years; P=2.06×10−5). In addition, the prognostic value of the progression-associated eight-lncRNA signature was independent of known clinical factors. Functional analysis suggested that eight prognostic lncRNAs may be involved in adipocytokine signaling pathway and glycerophospholipid metabolism. Taken together, the progression-associated eight-lncRNA signature identified by our study not only represents a candidate prognostic biomarker for LSCC patients but also provides insight into the molecular mechanisms in the progression of LSCC.

Aligning digital CD8+ scoring and targeted next-generation sequencing with programmed death ligand 1 expression: a pragmatic approach in early-stage squamous cell lung carcinoma.

To study programmed death ligand 1 (PD-L1) expression, tumour-infiltrating T lymphocytes (TILs) and the molecular context in patients with early-stage squamous cell lung carcinomas (SCCs). The study included samples from 40 patients (discovery cohort) and 29 patients (validation cohort) diagnosed with early-stage SCC. PD-L1 immunohistochemistry (IHC) was performed with three commercially available clones (E1L3N, SP263 and SP142). CD8+ TILs were scored with a digital algorithm. All tumours were analysed with targeted next-generation sequencing (NGS). Additionally, TP53 mutations were investigated with direct sequencing. In both cohorts, we observed a significant association between CD8+ TILs density and high PD-L1 IHC expression in tumour cells (TCs). Furthermore, high SP142 PD-L1 expression in immune cells (ICs) was also associated significantly with CD8+ TILs density. Therefore, CD8+ TILs density discriminated between patients with high versus low PD-L1 IHC expression with excellent sensitivity and specificity. Interestingly, the highest percentages of PD-L1-positive TCs with the three antibodies were found in samples with cyclin-dependent kinase 6 (CDK6) amplification, with high amplification of proto-oncogene C-Myc (CMYC) or with cyclin D1-PI3 kinase subunit alpha (CCND1-PIK3CA) co-amplification. High SP142 PD-L1 IHC expression in ICs showed a non-significant correlation with TP53 mutations. Conversely, most cases with fibroblast growth factor receptor 1 (FGFR1) amplification were negative for all PD-L1 clones. Our preliminary results support the use of digital CD8+ TILs scoring and targeted NGS alongside PD-L1 expression. The approach presented herein could help define patients with SCCs candidates to immune checkpoints inhibitors.

MA 13.02 Comprehensive Genetic Analysis Related to PD-L1 Expression in Early-stage Lung Squamous Cell Carcinoma

MA 13.02 Comprehensive Genetic Analysis Related to PD-L1 Expression in Early-stage Lung Squamous Cell Carcinoma