Commercially available prognostic molecular models in early-stage lung cancer: a review of the Pervenio Lung RS and Myriad myPlan Lung Cancer tests

DNA Damage Response Gene-Based Subtypes Associated With Clinical Outcomes in Early-Stage Lung Adenocarcinoma

DNA damage response (DDR) pathways play a crucial role in lung cancer. In this retrospective analysis, we aimed to develop a prognostic model and molecular subtype based on the expression profiles of DDR-related genes in early-stage lung adenocarcinoma (LUAD). A total of 1,785 lung adenocarcinoma samples from one RNA-seq dataset of The Cancer Genome Atlas (TCGA) and six microarray datasets of Gene Expression Omnibus (GEO) were included in the analysis. In the TCGA dataset, a DNA damage response gene (DRG)–based signature consisting of 16 genes was constructed to predict the clinical outcomes of LUAD patients. Patients in the low-DRG score group had better outcomes and lower genomic instability. Then, the same 16 genes were used to develop DRG-based molecular subtypes in the TCGA dataset to stratify early-stage LUAD into two subtypes (DRG1 and DRG2) which had significant differences in clinical outcomes. The Kappa test showed good consistency between molecular subtype and DRG (K = 0.61, p < 0.001). The DRG subtypes were significantly associated with prognosis in the six GEO datasets (pooled estimates of hazard ratio, OS: 0.48 (0.41–0.57), p < 0.01; DFS: 0.50 (0.41–0.62), p < 0.01). Furthermore, patients in the DRG2 group benefited more from adjuvant therapy than standard-of-care, which was not observed in the DRG1 group. In summary, we constructed a DRG-based molecular subtype that had the potential to predict the prognosis of early-stage LUAD and guide the selection of adjuvant therapy for early-stage LUAD patients.

Molecular Analysis of ZNF71 KRAB in Non-Small-Cell Lung Cancer

Our previous study found that zinc finger protein 71 (ZNF71) mRNA expression was associated with chemosensitivity and its protein expression was prognostic of non-small-cell lung cancer (NSCLC). The Krüppel associated box (KRAB) transcriptional repression domain is commonly present in human zinc finger proteins, which are linked to imprinting, silencing of repetitive elements, proliferation, apoptosis, and cancer. This study revealed that ZNF71 KRAB had a significantly higher expression than the ZNF71 KRAB-less isoform in NSCLC tumors (n = 197) and cell lines (n = 117). Patients with higher ZNF71 KRAB expression had a significantly worse survival outcome than patients with lower ZNF71 KRAB expression (log-rank p = 0.04; hazard ratio (HR): 1.686 [1.026, 2.771]), whereas ZNF71 overall and KRAB-less expression levels were not prognostic in the same patient cohort. ZNF71 KRAB expression was associated with epithelial-to-mesenchymal transition (EMT) in both patient tumors and cell lines. ZNF71 KRAB was overexpressed in NSCLC cell lines resistant to docetaxel and paclitaxel treatment compared to chemo-sensitive cell lines, consistent with its association with poor prognosis in patients. Therefore, ZNF71 KRAB isoform is a more effective prognostic factor than ZNF71 overall and KRAB-less expression for NSCLC. Functional analysis using CRISPR-Cas9 and RNA interference (RNAi) screening data indicated that a knockdown/knockout of ZNF71 did not significantly affect NSCLC cell proliferation in vitro.

Identification of a novel gene expression signature associated with overall survival in patients with lung adenocarcinoma: A comprehensive analysis based on TCGA and GEO databases

OBJECTIVES

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of clinical significance. This study aimed to identify novel molecular markers associated with LUAD prognosis.

MATERIALS AND METHODS

RNA sequencing data from the Cancer Genome Atlas (TCGA) database of LUAD tumors and paired normal tissues, and microarray data from the Gene Expression Omnibus (GEO) database were obtained. In the TCGA dataset, differentially expressed (DE) genes were identified by comparing gene expression between early-stage tumors and normal tissue, as well as between advanced-stage and early-stage tumors. A risk score was developed using a weighted linear combination of individual dysregulated protein-coding genes that was associated with overall survival (OS). The prognostic value of the risk score was evaluated using Kaplan-Meier and multivariate Cox analysis. The gene signature was further validated using independent datasets from GEO.

RESULTS

Among the 68 identified DE genes, 19 were individually associated with OS in univariate analyses. A risk score was constructed for each patient based on the coefficients in multivariate Cox model and normalized expression levels of these 19 genes. LUAD patients with a low risk score had a significantly better survival than those with a high risk score (log-rank P < 0.0001). After adjusting for age, sex, clinical stage, smoking history, and treatments, the patients with a low risk score had a 81 % decreased risk for death, compared to those with a high risk score (hazard ratio 0.19, 95 % confidence interval 0.097-0.36). The significant association of the risk score with OS in LUAD patients was further validated in three independent GEO datasets.

CONCLUSION

A novel 19-gene prognostic signature based on gene expression was identified in LUAD patients. The findings further improve the understanding of LUAD prognostication and have the potential to facilitate risk-stratified disease management.

Multi-Institutional Prospective Validation of Prognostic mRNA Signatures in Early Stage Squamous Lung Cancer (Alliance)

INTRODUCTION

Surgical resection is curative for some patients with early lung squamous cell carcinoma. Staging and clinical factors do not adequately predict recurrence risk. We sought to validate the discriminative performance of proposed prognostic gene expression signatures at a level of rigor sufficient to support clinical use.

METHODS

The two-stage validation used independent core laboratories, objective quality control standards, locked test parameters, and large multi-institutional specimen and data sets. The first stage validation confirmed a signature's ability to stratify patient survival. The second-stage validation determined which signature(s) optimally improved risk discrimination when added to baseline clinical predictors. Participants were prospectively enrolled in institutional (cohort I) or cooperative group (cohort II) biospecimen and data collection protocols. All cases underwent a central review of clinical, pathologic, and biospecimen parameters using objective criteria to determine final inclusion (cohort I: n = 249; cohort II: n = 234). Primary selection required that a signature significantly predict a 3-year survival after surgical resection in cohort I. Signatures meeting this criterion were further tested in cohort II, comparing risk prediction using baseline risk factors alone versus in combination with the signature.

RESULTS

Male sex, advanced age, and higher stage were associated with shorter survival in cohort I and established a baseline clinical model. Of the three signatures validated in cohort I, one signature was validated in cohort II and statistically significantly enhanced the prognosis relative to the baseline model (C-index difference 0.122; p < 0.05).

CONCLUSIONS

These results represent the first rigorous validation of a test appropriate to direct adjuvant treatment or clinical trials for patients with lung squamous cell carcinoma.

A novel diagnostic system to evaluate epidermal growth factor receptor impact as a prognostic and therapeutic indicator for lung adenocarcinoma

Many driver pathways for cancer cell proliferation have been reported. Driver pathway activation is often evaluated based on a single hotspot mutation such as EGFR L858R. However, because of complex intratumoral networks, the impact of a driver pathway cannot be predicted based on only a single gene mutation. Here, we developed a novel diagnostic system named the "EGFR impact score" which is based on multiplex mRNA expression profiles, which can predict the impact of the EGFR pathway in lung cancer cells and the effect of EGFR-tyrosine kinase inhibitors on malignancy. The EGFR impact score indicated robust predictive power for the prognosis of early-stage lung cancer because this score can evaluate the impact of the EGFR pathway on the tumor and genomic instability. Additionally, the molecular features of the poor prognostic group resembled those of biomarkers associated with immune checkpoint inhibitors. The EGFR impact score is a novel prognostic and therapeutic indicator for lung adenocarcinoma.

Effects of different doses of cisatracurium besilate on hemodynamics and postoperative cognitive function in patients undergoing radical resection of lung cancer

The effects of different doses of cisatracurium besilate on perioperative hemodynamics and early postoperative cognitive function in patients undergoing radical resection of lung cancer were investigated. One hundred and thirty-six patients who underwent radical resection of lung cancer from June 2013 to June 2016 in Dongying People's Hospital were retrospectively analyzed. Patients who were not given atracurium were selected as the control group (n=35). According to the different anesthetic doses, patients in the experimental group were separated into low dose (0.15 mg/kg cisatracurium besilate) group (LD group, n=34), medium dose (0.2 mg/kg cisatracurium besilate) group (MD group, n=36) and high dose (0.3 mg/kg cisatracurium besilate) group (HD group, n=31). The mean arterial pressure and heart rate (HR) were recorded before induction of anesthesia (T0), at the time of entering pleural cavity (T1), at the end of surgery (T2), and 1 day after surgery (T3). The Mini-Mental State Examination (MMSE) was used to evaluate the postoperative cognitive function scores of the 4 groups 1 day before operation and on the 1st, 3rd and 7th day after surgery. The agitation of patients at 6 and 12 h after operation was evaluated by Ramsay sedation score. There was no significant difference in arterial pressure among the four groups at T2 and T3 (P>0.05). There was no significant difference in terms of MMSE among the four groups 1 day before operation, 3 days after operation and 7 days after operation, but the MMSE score of the control group was significantly lower than that of the LD, MD and HD groups 1 day after surgery (P<0.05). Therefore, cisatracurium besilate can stabilize hemodynamics during radical operation of lung cancer and reduce the incidence of postoperative cognitive dysfunction, and it has no close association with the dose.

Prognostic Values of Platelet-Associated Indicators in Resectable Lung Cancers

Background:

Lung cancer is the leading cause of cancer death. Platelet-related indictors, including platelet count, plateletcrit, mean platelet volume, and platelet distribution width, not only associate with morphology and functions of platelet but also correlate with tumor development and metastasis. In the present study, we investigated the values of platelet-related indictors in the prognosis evaluation of resectable lung cancers.

Methods:

In total, 101 patients with resectable lung cancer were recruited in this study. Patients were divided into 2 groups according to the median pretreatment values. To evaluate the individual value changes after treatment, we introduced the concept of post-/pretreatment ratio (≤1 indicated value was not increased after treatment, while >1 suggested increased value).

Results:

The high pretreatment platelet count level was correlated with larger tumor size. High pretreatment plateletcrit level was associated with more lymph nodes metastasis. Patients with high pretreatment plateletcrit level had worse overall survival, whereas pretreatment platelet count, mean platelet volume, and platelet distribution width levels were not correlated with outcomes. Surgery had no impact on the values of platelet count, plateletcrit, mean platelet volume, or platelet distribution width. Adjuvant chemotherapy significantly decreased the values of platelet count and plateletcrit, whereas it had no effect on the values of mean platelet volume or platelet distribution width. Whole course of treatment (surgery combined with adjuvant chemotherapy) significantly decreased the values of platelet count and platelet distribution width, whereas it had no effect on the values of plateletcrit or mean platelet volume. Post-/pretreatment platelet count, plateletcrit, mean platelet volume, and platelet distribution width ratios were not correlated with outcomes. Univariate analyses demonstrated that American Joint Committee on Cancer stage and pretreatment plateletcrit level were significant risk factors for prognosis. Cox regression analysis revealed that no factor independently associated with worse survival.

Conclusion:

Pretreatment plateletcrit level could be a potential prognostic factor in resectable lung cancers.

Changes in store for early-stage non-small cell lung cancer

The management of advanced non-small cell lung cancer (NSCLC) has been revolutionized in recent years with the introduction of biomarker-targeted molecular therapies and immune checkpoint inhibitors. In contrast, since adjuvant chemotherapy was first established twenty years ago as the standard of care, little has changed for resected early-stage (IB-IIIA) patients for whom the potential for cure is greatest. In this manuscript we will review recently presented data as well as ongoing/planned studies in this arena. So far, investigative efforts have yielded mixed results regarding the use of tyrosine kinase inhibitors (TKIs) in early-stage NSCLC, though a series of now better planned, biomarker-driven ongoing phase III trials may be more informative. Several innovative immunotherapy studies have already shown promising results principally in the neoadjuvant setting with a large number of pivotal neo-adjuvant and adjuvant trials now in progress. Given the more robust design and biomarker-focused approach of the new generation of studies, significant advances in the optimal curative treatment of early stage NSCLC are anticipated.

Histology-dependent prognostic role of pERK and p53 protein levels in early-stage non-small cell lung cancer

Lung tumors represent a major health problem. In early stage NSCLC tumors, surgical resection is the preferred treatment, but 30-55% of patients will relapse within 5 years after surgery. Thus, the identification of prognostic biomarkers in early stage NSCLC patients, especially those which are therapeutically addressable, is crucial to enhance survival of these patients. We determined the immunohistochemistry expression of key proteins involved in tumorigenesis and oncogenic signaling, p53, EGFR, pAKT and pERK, and correlated their expression level to clinicopathological characteristics and patient outcome. We found EGFR expression is higher in the squamous cell carcinomas than in adenocarcinomas (p=0.043), and that nuclear p53 staining correlated with lower differentiated squamous tumors (p=0.034). Regarding the prognostic potential of the expression of these proteins, high pERK levels proved to be an independent prognostic factor for overall (p<0.001) and progression-free survival (p<0.001) in adenocarcinoma patients, but not in those from the squamous histology, and high p53 nuclear levels were identified as independent prognostic factor for progression-free survival (p=0.031) only in squamous cell carcinoma patients. We propose a role as early prognostic biomarkers for pERK protein levels in adenocarcinoma, and for nuclear p53 levels in squamous cell lung carcinoma. The determination of these potential biomarkers in the adequate histologic context may predict the outcome of early stage NSCLC patients, and may offer a therapeutic opportunity to enhance survival of these patients.

Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non-Small Cell Lung Cancer

Importance

The prevalence of early-stage non-small cell lung cancer (NSCLC) is expected to increase with recent implementation of annual screening programs. Reliable prognostic biomarkers are needed to identify patients at a high risk for recurrence to guide adjuvant therapy.

Objective

To develop a robust, individualized immune signature that can estimate prognosis in patients with early-stage nonsquamous NSCLC.

Design, Setting, and Participants

This retrospective study analyzed the gene expression profiles of frozen tumor tissue samples from 19 public NSCLC cohorts, including 18 microarray data sets and 1 RNA-Seq data set for The Cancer Genome Atlas (TCGA) lung adenocarcinoma cohort. Only patients with nonsquamous NSCLC with clinical annotation were included. Samples were from 2414 patients with nonsquamous NSCLC, divided into a meta-training cohort (729 patients), meta-testing cohort (716 patients), and 3 independent validation cohorts (439, 323, and 207 patients). All patients underwent surgery with a negative surgical margin, received no adjuvant or neoadjuvant therapy, and had publicly available gene expression data and survival information. Data were collected from July 22 through September 8, 2016.

Main Outcomes and Measures

Overall survival.

Results

Of 2414 patients (1205 men [50%], 1111 women [46%], and 98 of unknown sex [4%]; median age [range], 64 [15-90] years), a prognostic immune signature of 25 gene pairs consisting of 40 unique genes was constructed using the meta-training data set. In the meta-testing and validation cohorts, the immune signature significantly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I, IA, IB, or II disease and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.72 [95% CI, 1.26-2.33; P < .001] to 2.36 [95% CI, 1.47-3.79; P < .001]) after adjusting for clinical and pathologic factors. Several biological processes, including chemotaxis, were enriched among genes in the immune signature. The percentage of neutrophil infiltration (5.6% vs 1.8%) and necrosis (4.6% vs 1.5%) was significantly higher in the high-risk immune group compared with the low-risk groups in TCGA data set (P < .003). The immune signature achieved a higher accuracy (mean concordance index [C-index], 0.64) than 2 commercialized multigene signatures (mean C-index, 0.53 and 0.61) for estimation of survival in comparable validation cohorts. When integrated with clinical characteristics such as age and stage, the composite clinical and immune signature showed improved prognostic accuracy in all validation data sets relative to molecular signatures alone (mean C-index, 0.70 vs 0.63) and another commercialized clinical-molecular signature (mean C-index, 0.68 vs 0.65).

Conclusions and Relevance

The proposed clinical-immune signature is a promising biomarker for estimating overall survival in nonsquamous NSCLC, including early-stage disease. Prospective studies are needed to test the clinical utility of the biomarker in individualized management of nonsquamous NSCLC.

Prognostic and predictive biomarkers post curative intent therapy

Large-scale screening trials have demonstrated that early diagnosis of lung cancer results in a significant reduction in lung cancer mortality. Despite improvements in detecting more lung cancers at early stages, the 5-year survival rates of lung cancers diagnosed before widespread disease is only 30-50%. High rates of recurrence, despite early diagnosis, suggest the need to improve treatment strategies based on the likelihood of recurrence in patient subsets, as well as explore the role of predictive markers for therapy selection in the adjuvant setting. In the era of personalized medicine, there have been a wide array of molecular alterations and signatures studied for their potential prognostic and predictive utility, however most have failed to translate into clinical tools. This review will discuss progress made in clinical management of lung cancer, and recent progress in the development of patient selection tools for the refinement of early stage lung cancers.

Correlation between p-STAT3 overexpression and prognosis in lung cancer: A systematic review and meta-analysis

Objective

Previous studies have shown the correlation between p-STAT3 overexpression and prognosis in a variety of human tumors. However, their correlation in lung cancer remains controversial. We performed a systematic review and meta-analysis to explore the correlation between p-STAT3 overexpression and prognosis in lung cancer patients.

Methods

We searched PubMed, Embase, Web of Science, CNKI, VIP, and WanFang Data to identify relevant studies. Two reviewers independently screened the literature search results, extracted data, and assessed the methodological quality of the included studies. Then, meta-analysis was performed by using Review Manager 5.3 and STATA 14 software. A random-effect model was employed to evaluate all related pooled results. Statistical heterogeneity of each study was assessed by I². Publication bias was determined by funnel plot and the Begg’s or Egger’s tests.

Results

Eventually, 13 studies were included in present meta-analysis. Among these 13 studies, 8 studies were associated with the overall survival of lung cancer and 10 studies with other clinicopathological characteristics. The results of this meta-analysis suggested that p-STAT3 overexpression may be a poor prognosis biomarker in lung cancer (HR: 1.23; 95% CI: 1.04–1.46; P = 0.02). In terms of other clinicopathological characteristics, p-STAT3 overexpression was more frequent to advanced TNM stages ranging from III to IV (OR: 1.92; 95% CI: 1.13–3.27; P = 0.02) and lymphatic node metastasis (OR: 1.81; 95% CI: 1.20–2.72; P = 0.004). But, it was not associated with tumor differentiation (OR: 0.82; 95% CI: 0.44–1.53; P = 0.54).

Conclusion

p-STAT3 overexpression has significant correlation with poorer overall survival of lung cancer patients, as well as with more advanced TNM stages and lymph node metastasis. Thus, it may serve a biomarker for poor prognosis in lung cancer. Nevertheless, our findings should be confirmed by large prospective studies.

Integration of multiple "OMIC" biomarkers: A precision medicine strategy for lung cancer

More than half of all new lung cancer diagnoses are made in patients with locally advanced or metastatic disease, at which point therapeutic options are scarce. It is anticipated, however, that the widespread use of Low-Dose Computed Tomography (LDCT) screening, will lead to a greater proportion of lung cancers being diagnosed at an early, operable, stage. Still, the overall rate of recurrence for surgically treated Stage I lung cancer patients is up to 30% within 5 years of diagnosis. Thus, the identification and clinical application of biomarkers of early stage lung cancer are a pressing medical need. The integrative analysis of "omic," clinical and epidemiological data for single patients is a core principle of precision medicine. Through rigorous bioinformatics and statistical analyses we have identified biomarkers of early-stage lung cancer based on DNA methylation, expression of mRNA and miRNA, inflammatory cytokines, and urinary metabolites. Beyond a more comprehensive understanding of the molecular taxonomy of lung cancer, these biomarkers can have very practical implications in the context of unmet clinical needs of early stage lung cancer patients: First, current guidelines for LDCT screening broadly include individuals based on age and history of heavy smoking. Tumor-derived circulating biomarkers in the blood and urine associated with lung cancer risk could narrow and prioritize individuals for LDCT screening. Second, a high number of nodules are identified by LDCT, of which fewer than 5% are finally diagnosed as lung cancer. Biomarkers may help discriminate malignant nodules from benign or indolent lesions. Third, the expected rise in the numbers of lung cancer patients diagnosed at an early stage will necessitate new treatment options. Circulating, urinary and tissue-based biomarkers that molecularly categorize Stage I patients after tumor resection can help identify high-risk patients who may benefit from adjuvant chemotherapy or innovative immunotherapy regimens.

Development of a RNA-Seq Based Prognostic Signature in Lung Adenocarcinoma

Background

Precision therapy for lung cancer will require comprehensive genomic testing to identify actionable targets as well as ascertain disease prognosis. RNA-seq is a robust platform that meets these requirements, but microarray-derived prognostic signatures are not optimal for RNA-seq data. Thus, we undertook the first prognostic analysis of lung adenocarcinoma RNA-seq data and generated a prognostic signature.

Methods

Lung adenocarcinoma RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) were divided chronologically into training (n = 255) and validation (n = 157) cohorts. In the training cohort, prognostic association was assessed by univariate Cox analysis. A prognostic signature was built with stepwise multivariable Cox analysis. Outcomes by risk group, stage, and mutation status were analyzed with Kaplan-Meier and multivariable Cox analyses. All the statistical tests were two-sided.

Results

In the training cohort, 96 genes had prognostic association with P values of less than or equal to 1.00x10^-4, including five long noncoding RNAs (lncRNAs). Stepwise regression generated a four-gene signature, including one lncRNA. Signature high-risk cases had worse overall survival (OS) in the TCGA validation cohort (hazard ratio [HR] = 3.07, 95% confidence interval [CI] = 2.00 to 14.62) and a University of Michigan institutional cohort (n = 67; HR = 2.05, 95% CI = 1.18 to 4.55), and worse metastasis-free survival in the TCGA validation cohort (HR = 3.05, 95% CI = 2.31 to 13.37). The four-gene prognostic signature also statistically significantly stratified overall survival in important clinical subsets, including stage I (HR = 2.78, 95% CI = 1.91 to 11.13), EGFR wild-type (HR = 3.01, 95% CI = 1.73 to 14.98), and EGFR mutant (HR = 8.99, 95% CI = 62.23 to 141.44). The four-gene prognostic signature also stood out on top when compared with other prognostic signatures.

Conclusions

Here, we present the first RNA-seq prognostic signature for lung adenocarcinoma that can provide a powerful prognostic tool for precision oncology as part of an integrated RNA-seq clinical sequencing program.

Evaluating genotoxic risks in Brazilian public health agents occupationally exposed to pesticides: a multi-biomarker approach

This is the first study demonstrating genotoxic effects and whole transcriptome analysis on community health agents (CHAs) occupationally exposed to pesticides in Central Brazil. For the transcriptome analysis, we found some genes related to Alzheimer's disease (LRP1), an insulin-like growth factor receptor (IGF2R), immunity genes (IGL family and IGJ), two genes related to inflammatory reaction (CXCL5 and CCL3), one gene related to maintenance of cellular morphology (NHS), one gene considered to be a strong apoptosis inductor (LGALS14), and several transcripts of the neuroblastoma breakpoint family (NBPF). Related to comet assay, we demonstrated a significant increase in DNA damage, measured by the olive tail moment (OTM), in the exposed group compared to the control group. Moreover, we also observed a statistically significant difference in OTM values depending on GSTM1 genotypes. Therefore, Brazilian epidemiological surveillance, an organization responsible for the assessment and management of health risks associated to pesticide exposure to CHA, needs to be more proactive and considers the implications of pesticide exposure for CHA procedures and processes.