Germline polymorphisms and survival of lung adenocarcinoma patients: a genome-wide study in two European patient series

Germline Whole-Exome Sequencing in Non-Smoker Lung Cancer Patients Reveals Pathogenic Variants in Lung Cancer Driver Genes

Approximately 10%-15% of all lung cancers arise in non-smokers. Although there are no established aetiological factors, non-smokers with a family history of cancer have an increased risk of lung cancer, implying host genetic factors in lung cancer susceptibility. We sought to identify, in a cohort of 75 patients recruited before lung lobectomy, germline alterations with a strong association with lung cancer. Whole-exome sequencing was performed on genomic DNA from peripheral blood. Six resources were used to select pathogenic germline variants with strong clinical significance. In total, 33 pathogenic or likely pathogenic variants in 31 genes were identified. Of these, 13 were located in cancer-predisposing genes (nine were lung cancer drivers), most of which were involved in DNA repair mechanisms and diseases of metabolism. Among DNA repair-related genes, BRCA1 and BRCA2, and ATM have also been identified in other studies on non-smokers. Our results strongly support the hypothesis that a number of non-smoker lung cancer patients carry germline variants in cancer-predisposing genes, suggesting that lung cancer patients, particularly non-smokers, should be considered for germline molecular testing.

The prognostic value of radiogenomics using CT in patients with lung cancer: a systematic review

This systematic review aimed to evaluate the effectiveness of combining radiomic and genomic models in predicting the long-term prognosis of patients with lung cancer and to contribute to the further exploration of radiomics. This study retrieved comprehensive literature from multiple databases, including radiomics and genomics, to study the prognosis of lung cancer. The model construction consisted of the radiomic and genomic methods. A comprehensive bias assessment was conducted, including risk assessment and model performance indicators. Ten studies between 2016 and 2023 were analyzed. Studies were mostly retrospective. Patient cohorts varied in size and characteristics, with the number of patients ranging from 79 to 315. The construction of the model involves various radiomic and genotic datasets, and most models show promising prediction performance with the area under the receiver operating characteristic curve (AUC) values ranging from 0.64 to 0.94 and the concordance index (C-index) values from 0.28 to 0.80. The combination model typically outperforms the single method model, indicating higher prediction accuracy and the highest AUC was 0.99. Combining radiomics and genomics in the prognostic model of lung cancer may improve the predictive performance. However, further research on standardized data and larger cohorts is needed to validate and integrate these findings into clinical practice. CRITICAL RELEVANCE STATEMENT: The combination of radiomics and genomics in the prognostic model of lung cancer improved prediction accuracy in most included studies. KEY POINTS: The combination of radiomics and genomics can improve model performance in most studies. The results of establishing prognosis models by different methods are discussed. The combination of radiomics and genomics may be helpful to provide better treatment for patients.

Germline Polymorphisms Associated with Overall Survival in Lung Adenocarcinoma: Genome-Wide Analysis

BACKGROUND/OBJECTIVES

Lung cancer remains a global health concern, with substantial variation in patient survival. Despite advances in detection and treatment, the genetic basis for the divergent outcomes is not understood. We investigated germline polymorphisms that modulate overall survival in 1464 surgically resected lung adenocarcinoma patients.

METHODS

A multivariable Cox proportional hazard model was used to assess the association of more than seven million polymorphisms with overall survival at the 60-month follow-up, considering age, sex, pathological stage, decade of surgery and principal components as covariates. Genes in which variants were identified were studied in silico to investigate functional roles.

RESULTS

Six germline variants passed the genome-wide significance threshold. These single nucleotide polymorphisms were mapped to non-coding (intronic) regions on chromosomes 2, 3, and 5. The minor alleles of rs13000315, rs151212827, and rs190923216 (chr. 2, 3 and 5, respectively) were found to be independent negative prognostic factors. All six variants have been reported to regulate the expression of nine genes, seven of which are protein-coding, in different tissues. Survival-associated variants on chromosomes 2 and 3 were already reported to regulate the expression of NT5DC2 and NAGK, with high expression associated with the minor alleles. High NT5DC2 and NAGK expression in lung adenocarcinoma tissue was already shown to correlate with poor overall survival.

CONCLUSIONS

This study highlights a potential regulatory role of the identified polymorphisms in influencing outcome and suggests a mechanistic link between these variants, gene expression regulation, and lung adenocarcinoma prognosis. Validation and functional studies are warranted to elucidate the mechanisms underlying these associations.

Single nucleotide variants in lung cancer

Germline genetic variants, including single-nucleotide variants (SNVs) and copy number variants (CNVs), account for interpatient heterogeneity. In the past several decades, genome-wide association studies (GWAS) have identified multiple lung cancer-associated SNVs in Caucasian and Chinese populations. These variants either reside within coding regions and change the structure and function of cancer-related proteins or reside within non-coding regions and alter the expression level of cancer-related proteins. The variants can be used not only for cancer risk assessment and prevention but also for the development of new therapies. In this review, we discuss the lung cancer-associated SNVs identified to date, their contributions to lung tumorigenesis and prognosis, and their potential use in predicting prognosis and implementing therapeutic strategies.

Lung Adenocarcinoma Diagnosed at a Younger Age Is Associated with Advanced Stage, Female Sex, and Ever-Smoker Status, in Patients Treated with Lung Resection

To date, the factors which affect the age at diagnosis of lung adenocarcinoma are not fully understood. In our study, we examined the relationships of age at diagnosis with smoking, pathological stage, sex, and year of diagnosis in a discovery (n = 1694) and validation (n = 1384) series of lung adenocarcinoma patients who had undergone pulmonary resection at hospitals in the Milan area and at Thoraxklinik (Heidelberg), respectively. In the discovery series, younger age at diagnosis was associated with ever-smoker status (OR = 1.5, p = 0.0035) and advanced stage (taking stage I as reference: stage III OR = 1.4, p = 0.0067; stage IV OR = 1.7, p = 0.0080), whereas older age at diagnosis was associated with male sex (OR = 0.57, p < 0.001). Analysis in the validation series confirmed the ever versus never smokers' association (OR = 2.9, p < 0.001), the association with highest stages (stage III versus stage I OR = 1.4, p = 0.0066; stage IV versus stage I OR = 2.0, p = 0.0022), and the male versus female sex association (OR = 0.78, p = 0.032). These data suggest the role of smoking in affecting the natural history of the disease. Moreover, aggressive tumours seem to have shorter latency from initiation to clinical detection. Finally, younger age at diagnosis is associated with the female sex, suggesting that hormonal status of young women confers risk to develop lung adenocarcinoma. Overall, this study provided novel findings on the mechanisms underlying age at diagnosis of lung adenocarcinoma.

Genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue

Emerging evidence suggests that the prognosis of patients with lung adenocarcinoma can be determined from germline variants and transcript levels in nontumoral lung tissue. Gene expression data from noninvolved lung tissue of 483 lung adenocarcinoma patients were tested for correlation with overall survival using multivariable Cox proportional hazard and multivariate machine learning models. For genes whose transcript levels are associated with survival, we used genotype data from 414 patients to identify germline variants acting as cis-expression quantitative trait loci (eQTLs). Associations of eQTL variant genotypes with gene expression and survival were tested. Levels of four transcripts were inversely associated with survival by Cox analysis (CLCF1, hazard ratio [HR] = 1.53; CNTNAP1, HR = 2.17; DUSP14, HR = 1.78; and MT1F: HR = 1.40). Machine learning analysis identified a signature of transcripts associated with lung adenocarcinoma outcome that was largely overlapping with the transcripts identified by Cox analysis, including the three most significant genes (CLCF1, CNTNAP1, and DUSP14). Pathway analysis indicated that the signature is enriched for ECM components. We identified 32 cis-eQTLs for CNTNAP1, including 6 with an inverse correlation and 26 with a direct correlation between the number of minor alleles and transcript levels. Of these, all but one were prognostic: the six with an inverse correlation were associated with better prognosis (HR < 1) while the others were associated with worse prognosis. Our findings provide supportive evidence that genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue.

Gene Expression Landscape of Chronic Myeloid Leukemia K562 Cells Overexpressing the Tumor Suppressor Gene PTPRG

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context.

Acute Myeloid Leukemia: New Multiomics Molecular Signatures and Implications for Systems Medicine Diagnostics and Therapeutics Innovation

Acute myeloid leukemia (AML) is a common, complex, and multifactorial malignancy of the hematopoietic system. AML diagnosis and treatment outcomes display marked heterogeneity and patient-to-patient variations. To date, AML-related biomarker discovery research has employed single omics inquiries. Multiomics analyses that reconcile and integrate the data streams from multiple levels of the cellular hierarchy, from genes to proteins to metabolites, offer much promise for innovation in AML diagnostics and therapeutics. We report, in this study, a systems medicine and multiomics approach to integrate the AML transcriptome data and reporter biomolecules at the RNA, protein, and metabolite levels using genome-scale biological networks. We utilized two independent transcriptome datasets (GSE5122, GSE8970) in the Gene Expression Omnibus database. We identified new multiomics molecular signatures of relevance to AML: miRNAs (e.g., mir-484 and miR-519d-3p), receptors (ACVR1 and PTPRG), transcription factors (PRDM14 and GATA3), and metabolites (in particular, amino acid derivatives). The differential expression profiles of all reporter biomolecules were crossvalidated in independent RNA-Seq and miRNA-Seq datasets. Notably, we found that PTPRG holds important prognostication potential as evaluated by Kaplan-Meier survival analyses. The multiomics relationships unraveled in this analysis point toward the genomic pathogenesis of AML. These multiomics molecular leads warrant further research and development as potential diagnostic and therapeutic targets.

Integrated Multi-Omics Analysis Identified PTPRG and CHL1 as Key Regulators of Immunophenotypes in Clear Cell Renal Cell Carcinoma(ccRCC)

Despite the increasing importance and status of immune checkpoint blockade (ICB), little is known about the underlying molecular mechanisms determining the target clear cell renal cell carcinoma (ccRCC) population. In this study, we screened out 6 immune cells strongly correlated with expression levels of PD-L1 and IFN-γ based on the ccRCC samples extracted from GSE and TCGA data sets. By performing unsupervised clustering and lasso regression analysis, we grouped the ccRCC into 4 clusters and selected the two most distinct sub-clusters for further investigation-cluster A1 and B1. Next, we compared the two clusters in terms of mRNA, somatic mutations, copy number variations, DNA methylation, miRNA, lncRNA and constructed the differentially expressed genes (DEGs) hub by combing together the previous results at levels of DNA methylation, miRNA, and lncRNA. PTPRG and CHL1 were identified as key nodes in the regulation hub of immunophenotypes in ccRCC patients. Finally, we established the prognosis model by using Lasso-Cox regression and Kaplan-Meier analysis, recognizing WNT2, C17orf66, and PAEP as independent significant risk factors while IRF4 as an independent protective factor.

The Role of the Tumor Suppressor Gene Protein Tyrosine Phosphatase Gamma in Cancer

Members of the Protein Tyrosine Phosphatase (PTPs) family are associated with growth regulation and cancer development. Acting as natural counterpart of tyrosine kinases (TKs), mainly involved in crucial signaling pathways such as regulation of cell cycle, proliferation, invasion and angiogenesis, they represent key parts of complex physiological homeostatic mechanisms. Protein tyrosine phosphatase gamma (PTPRG) is classified as a R5 of the receptor type (RPTPs) subfamily and is broadly expressed in various isoforms in different tissues. PTPRG is considered a tumor-suppressor gene (TSG) mapped on chromosome 3p14-21, a region frequently subject to loss of heterozygosity in various tumors. However, reported mechanisms of PTPRG downregulation include missense mutations, ncRNA gene regulation and epigenetic silencing by hypermethylation of CpG sites on promoter region causing loss of function of the gene product. Inactive forms or total loss of PTPRG protein have been described in sporadic and Lynch syndrome colorectal cancer, nasopharyngeal carcinoma, ovarian, breast, and lung cancers, gastric cancer or diseases affecting the hematopoietic compartment as Lymphoma and Leukemia. Noteworthy, in Central Nervous System (CNS) PTPRZ/PTPRG appears to be crucial in maintaining glioblastoma cell-related neuronal stemness, carving out a pathological functional role also in this tissue. In this review, we will summarize the current knowledge on the role of PTPRG in various human cancers.

Tumor infiltrating lymphocyte signature is associated with single nucleotide polymorphisms and predicts survival in esophageal squamous cell carcinoma patients

Purpose: Esophageal cancer is the sixth leading cause of cancer-related death worldwide, and is associated with a poor prognosis. Stromal tumor infiltrating lymphocytes (sTIL) and certain single nucleotide polymorphisms (SNPs) have been found to be predictive of patient survival. In this study, we explored the association between SNPs and sTIL regarding the predictability of disease-free survival in patients with esophageal squamous cell carcinoma (ESCC).

Materials and methods: We collected 969 pathologically confirmed ESCC patients from 2010 to 2013 and genotyped 101 SNPs from 59 genes. The number of sTIL for each patient was determined using an automatic algorithm. A Kruskal-Wallis test was used to determine the association between genotype and sTIL. The genotypes and clinical factors related to survival were analyzed using a Kaplan-Meier curve, Cox proportional hazards model, and log-rank test.

Results: The median age of the patients was 67 (42-85 years), there was a median follow-up of 851.5 days and 586 patients died. The univariable analysis showed that 10 of the 101 SNPs were associated with sTIL. Six SNPs were also associated with disease-free survival. A multivariable analysis revealed that sTIL, rs1801131, rs25487, and rs8030672 were independent prognostic markers for ESCC patients. The model combining SNPs, clinical characteristics and sTIL outperformed the model with clinical characteristics alone for predicting outcomes in ESCC patients.

Conclusion: We discovered 10 SNPs associated with sTIL in ESCC and we built a model of sTIL, SNPs and clinical characteristics with improved prediction of survival in ESCC patients.

Difficulties in establishing a causal link between chemical exposures and cancer cannot be overcome by court assessments

Scientific data are often used in lawsuits to prove, or dismiss, causation by a claimed factor of a claimed disease. Recent media reports of million-dollar compensations awarded to some cancer patients who had been exposed to certain chemical substances motivated me to examine how solid the causal links really were. Here, I discuss the limitations of epidemiological research on cancer causation and highlight how new knowledge of cancer genetics makes it unrealistic to expect that cancer causation can be clearly demonstrated. I then present two exposure-cancer cases, namely talcum powder-ovarian cancer and glyphosate-non-Hodgkin lymphoma, that led to civil lawsuits decided, in the United States, in favor of the claimants. Both these cancers have several risk factors, among which the claimed exposure presents only a minor, if any, increased risk. Through these cases, I explain why the use of epidemiological data is inappropriate to define causal associations in complex diseases like cancer. I close by suggesting a fairer approach, called proportional liability, to resolving future cancer litigation cases.

Regulative Loop between β-catenin and Protein Tyrosine Receptor Type γ in Chronic Myeloid Leukemia

Protein tyrosine phosphatase receptor type γ (PTPRG) is a tumor suppressor gene, down-regulated in Chronic Myeloid Leukemia (CML) cells by the hypermethylation of its promoter region. β-catenin (CTNNB1) is a critical regulator of Leukemic Stem Cells (LSC) maintenance and CML proliferation. This study aims to demonstrate the antagonistic regulation between β-catenin and PTPRG in CML cells. The specific inhibition of PTPRG increases the activation state of BCR-ABL1 and modulates the expression of the BCR-ABL1- downstream gene β-Catenin. PTPRG was found to be capable of dephosphorylating β-catenin, eventually causing its cytosolic destabilization and degradation in cells expressing PTPRG. Furthermore, we demonstrated that the increased expression of β-catenin in PTPRG-negative CML cell lines correlates with DNA (cytosine-5)-methyl transferase 1 (DNMT1) over-expression, which is responsible for PTPRG promoter hypermethylation, while its inhibition or down-regulation correlates with PTPRG re-expression. We finally confirmed the role of PTPRG in regulating BCR-ABL1 and β-catenin phosphorylation in primary human CML samples. We describe here, for the first time, the existence of a regulative loop occurring between PTPRG and β-catenin, whose reciprocal imbalance affects the proliferation kinetics of CML cells.

Circular RNA cMras inhibits lung adenocarcinoma progression via modulating miR-567/PTPRG regulatory pathway

Objectives

Circular RNA, a type of RNA formed by a covalently closed loop, possesses sophisticated abilities of gene regulation in tumorigenesis and metastasis. However, the role of circRNAs on lung adenocarcinoma (LUAD) remains largely unknown.

Materials and methods

The role of cMras was examined both in vitro and in vivo. cMras expression in LUAD tissues was determined by quantitative real‐time PCR (qRT‐PCR). Downstream targets of cMras were predicted by bioinformatics tools and confirmed by RNA immunoprecipitation assay and luciferase assay. qRT‐PCR and western blot assay were used to detect the expression of specific targets.

Results

Thirty‐six paired LUAD and healthy tissues were collected and cMras resulted significantly downregulated in cancerous tissues. Its expression was negatively associated with tumour stages. cMras overexpression suppressed LUAD growth and metastasis, while endogenous cMras silencing resulted in the opposite effects. Bioinformatics analysis and experimental evidence confirmed that cMras was a sponge of miRNA‐567 and released its direct target, PTPRG. cMras overexpression decreased miR‐567 expression and subsequently increased PTPRG expression, while increased miRNA‐567 expression blocked the effects induced by cMras. Moreover, PTPRG was downregulated in LUAD and patients with low PTPRG expression exhibited significantly poor prognosis. These results suggested that cMras/miR‐567/PTPRG regulatory pathway might be associated to LUAD tumorigenesis and development.

Conclusions

A novel circular RNA cMras and its functions were identified, discovering a cMras/miR‐567/PTPRG regulatory pathway in LUAD tumorigenesis and development.

A missense variant in PTPN12 associated with the risk of colorectal cancer by modifying Ras/MEK/ERK signaling

BACKGROUND

The classical protein tyrosine phosphatases (PTPs) have been widely reported to be associated with various human malignancies including colorectal cancer (CRC). However, there are few comprehensive analyses of the association between the classical PTP genes and CRC risk.

METHODS

First, a bioinformatics analysis was performed to identify missense variants within the classical PTP gene family. Second, exome-wide association data and an independent population study were conducted to evaluate effects of candidate variants on CRC risk. Finally, functional assays based on signaling pathways were applied to uncover the potential pathogenic mechanism.

RESULTS

We identified that PTPN12 rs3750050 G allele presented a 19% increase the risk of CRC, with an OR of 1.19 (95% CI = 1.09-1.30, P =  1.015×10^-4) under an additive model in the combined analysis. Furthermore, biochemical assays illustrated that rs3750050 could impair the inhibitory effect of PTPN12 on Ras/MEK/ERK signaling by impeding SHC dephosphorylation, increase the expression of cyclin D1 and ultimately lead to aberrant cell proliferation, thus contributing to CRC pathogenesis.

CONCLUSION

Our study highlights that PTPN12 rs3750050 could increase CRC risk by modifying Ras/MEK/ERK signaling. This work provides a novel insight into the roles of genetic variants within PTP genes in the pathogenesis of CRC.

A Decade of GWAS Results in Lung Cancer

Genome-wide association studies (GWAS) were successful to identify genetic factors robustly associated with lung cancer. This review aims to synthesize the literature in this field and accelerate the translation of GWAS discoveries into results that are closer to clinical applications. A chronologic presentation of published GWAS on lung cancer susceptibility, survival, and response to treatment is presented. The most important results are tabulated to provide a concise overview in one read. GWAS have reported 45 lung cancer susceptibility loci with varying strength of evidence and highlighted suspected causal genes at each locus. Some genetic risk loci have been refined to more homogeneous subgroups of lung cancer patients in terms of histologic subtypes, smoking status, gender, and ethnicity. Overall, these discoveries are an important step for future development of new therapeutic targets and biomarkers to personalize and improve the quality of care for patients. GWAS results are on the edge of offering new tools for targeted screening in high-risk individuals, but more research is needed if GWAS are to pay off the investment. Complementary genomic datasets and functional studies are needed to refine the underlying molecular mechanisms of lung cancer preliminarily revealed by GWAS and reach results that are medically actionable. Cancer Epidemiol Biomarkers Prev; 27(4); 363-79. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Read-through transcripts in normal human lung parenchyma are down-regulated in lung adenocarcinoma

Read-through transcripts result from the continuous transcription of adjacent, similarly oriented genes, with the splicing out of the intergenic region. They have been found in several neoplastic and normal tissues, but their pathophysiological significance is unclear. We used high-throughput sequencing of cDNA fragments (RNA-Seq) to identify read-through transcripts in the non-involved lung tissue of 64 surgically treated lung adenocarcinoma patients. A total of 52 distinct read-through species was identified, with 24 patients having at least one read-through event, up to a maximum of 17 such transcripts in one patient. Sanger sequencing validated 28 of these transcripts and identified an additional 15, for a total of 43 distinct read-through events involving 35 gene pairs. Expression levels of 10 validated read-through transcripts were measured by quantitative PCR in pairs of matched non-involved lung tissue and lung adenocarcinoma tissue from 45 patients. Higher expression levels were observed in normal lung tissue than in the tumor counterpart, with median relative quantification ratios between normal and tumor varying from 1.90 to 7.78; the difference was statistically significant (P < 0.001, Wilcoxon's signed-rank test for paired samples) for eight transcripts: ELAVL1–TIMM44, FAM162B–ZUFSP, IFNAR2–IL10RB, INMT–FAM188B, KIAA1841–C2orf74, NFATC3–PLA2G15, SIRPB1–SIRPD, and SHANK3–ACR. This report documents the presence of read-through transcripts in apparently normal lung tissue, with inter-individual differences in patterns and abundance. It also shows their down-regulation in tumors, suggesting that these chimeric transcripts may function as tumor suppressors in lung tissue.

Genetic susceptibility variants for lung cancer: replication study and assessment as expression quantitative trait loci

Many single nucleotide polymorphisms (SNPs) have been associated with lung cancer but lack confirmation and functional characterization. We retested the association of 56 candidate SNPs with lung adenocarcinoma risk and overall survival in a cohort of 823 Italian patients and 779 healthy controls, and assessed their function as expression quantitative trait loci (eQTLs). In the replication study, eight SNPs (rs401681, rs3019885, rs732765, rs2568494, rs16969968, rs6495309, rs11634351, and rs4105144) associated with lung adenocarcinoma risk and three (rs9557635, rs4105144, and rs735482) associated with survival. Five of these SNPs acted as cis-eQTLs, being associated with the transcription of IREB2 (rs2568494, rs16969968, rs11634351, rs6495309), PSMA4 (rs6495309) and ERCC1 (rs735482), out of 10,821 genes analyzed in lung. For these three genes, we obtained experimental evidence of differential allelic expression in lung tissue, pointing to the existence of in-cis genomic variants that regulate their transcription. These results suggest that these SNPs exert their effects on cancer risk/outcome through the modulation of mRNA levels of their target genes.

Identification of hallmarks of lung adenocarcinoma prognosis using whole genome sequencing

In conjunction with clinical characteristics, prognostic biomarkers are essential for choosing optimal therapies to lower the mortality of lung adenocarcinoma. Whole genome sequencing (WGS) of 7 cancerous-noncancerous tissue pairs was performed to explore the comparative copy number variations (CNVs) associated with lung adenocarcinoma. The frequencies of top ranked CNVs were verified in an independent set of 114 patients and then the roles of target CNVs in disease prognosis were assessed in 313 patients. The WGS yielded 2604 CNVs. After frequency validation and biological function screening of top 10 CNVs, 9 mutant driver genes from 7 CNVs were further analyzed for an association with survival. Compared with the PBXIP1 amplified copy number, unamplified carriers had a 0.62-fold (95%CI = 0.43–0.91) decreased risk of death. Compared with an amplified TERT, those with an unamplified TERT had a 35% reduction (95% CI = 3%–56%) in risk of lung adenocarcinoma progression. Cases with both unamplified PBXIP1 and TERT had a median 34.32-month extension of overall survival and 34.55-month delay in disease progression when compared with both amplified CNVs. This study demonstrates that CNVs of TERT and PBXIP1 have the potential to translate into the clinic and be used to improve outcomes for patients with this fatal disease.

Cytochrome P450 Allele CYP3A7*1C Associates with Adverse Outcomes in Chronic Lymphocytic Leukemia, Breast, and Lung Cancer

CYP3A enzymes metabolize endogenous hormones and chemotherapeutic agents used to treat cancer, thereby potentially affecting drug effectiveness. Here, we refined the genetic basis underlying the functional effects of a CYP3A haplotype on urinary estrone glucuronide (E1G) levels and tested for an association between CYP3A genotype and outcome in patients with chronic lymphocytic leukemia (CLL), breast, or lung cancers. The most significantly associated SNP was rs45446698, an SNP that tags the CYP3A7*1C allele; this SNP was associated with a 54% decrease in urinary E1G levels. Genotyping this SNP in 1,008 breast cancer, 1,128 lung cancer, and 347 CLL patients, we found that rs45446698 was associated with breast cancer mortality (HR, 1.74; P = 0.03), all-cause mortality in lung cancer patients (HR, 1.43; P = 0.009), and CLL progression (HR, 1.62; P = 0.03). We also found borderline evidence of a statistical interaction between the CYP3A7*1C allele, treatment of patients with a cytotoxic agent that is a CYP3A substrate, and clinical outcome (Pinteraction = 0.06). The CYP3A7*1C allele, which results in adult expression of the fetal CYP3A7 gene, is likely to be the functional allele influencing levels of circulating endogenous sex hormones and outcome in these various malignancies. Further studies confirming these associations and determining the mechanism by which CYP3A7*1C influences outcome are required. One possibility is that standard chemotherapy regimens that include CYP3A substrates may not be optimal for the approximately 8% of cancer patients who are CYP3A7*1C carriers.