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Introduction: Lung cancer is a complex polygenic disorder. Analysis with Mendelian randomization (MR) allows for genetically predicted risks to be estimated between exposures and outcomes. Methods: We analyzed 345 heritable traits from the United Kingdom Biobank and estimated their associated effects on lung cancer outcomes using two sample MR. In addition to estimating effects with overall lung cancer, adenocarcinoma, small cell lung cancer, and squamous cell lung cancers, we performed conditional effect modeling with multivariate MR (MVMR) and the traits of alcohol use, smoking initiation, average pre-tax income, and educational attainment. Results: Univariate MR provided evidence for increased age at first sexual intercourse (OR, 0.55; P = 6.15 × 10-13), educational attainment (OR, 0.24; P = 1.07 × 10-19), average household income (OR, 0.58; P = 7.85 × 10-05), and alcohol usually taken with meals (OR, 0.19; P = 1.06 × 10-06) associating with decreased odds of overall lung cancer development. In contrast, a lack of additional educational attainment (OR, 8.00; P = 3.48 × 10-12), body mass index (OR, 1.28; P = 9.00 × 10-08), pack years smoking as a proportion of life span (OR, 9.93; P = 7.96 × 10-12), and weekly beer intake (OR, 3.48; P = 4.08 × 10-07) were associated with an increased risk of overall lung cancer development. Conclusions: Many heritable traits associated with an increased or inverse risk of lung cancer development. Effects vary based on histologic subtype and conditional third trait exposures. Impact: We identified several heritable traits and presented their genetically predictable impact on lung cancer development, providing valuable insights for consideration. [ABSTRACT FROM AUTHOR]

Background: It is estimated that 6% to 20% of all cholangiocarcinoma (CCA) diagnoses are explained by primary sclerosing cholangitis (PSC), but the underlying risk factors in the absence of PSC are unclear. We examined associations of different risk factors with intrahepatic cholangiocarcinoma (ICC) and extrahepatic cholangiocarcinoma (ECC) in the United States. Methods: We conducted a case-control study of 121 patients with ECC and 308 patients with ICC treated at MD Anderson Cancer Center between May 2014 and March 2020, compared with 1,061 healthy controls. Multivariable logistic regression analysis was applied to estimate the adjusted OR (AOR) and 95% confidence interval (CI) for each risk factor. Results: Being Asian, diabetes mellitus, family history of cancer, and gallbladder stones were associated with higher odds of developing ICC and ECC. Each 1-unit increase in body mass index in early adulthood (ages 20-40 years) was associated with a decrease in age at diagnosis of CCA (6.7 months, P < 0.001; 6.1 months for ICC, P = 0.001; 8.2 months for ECC, P = 0.007). A family history of cancer was significantly associated with the risk of ICC and ECC development; the AORs (95% CI) were 1.11 (1.06-1.48) and 1.32 (1.01-2.00) for ICC and ECC, respectively. Conclusions: In this study, early adulthood onset of obesity was significantly associated with CCA and may predict early diagnosis at younger age than normal weight individuals. Impact: The study highlights the association between obesity and CCA, independent of PSC. There is a need to consider the mechanistic pathways of obesity in the absence of fatty liver and cirrhosis. [ABSTRACT FROM AUTHOR]

Background: Tobacco exposure causes 8 of 10 lung cancers, and identifying additional risk factors is challenging due to confounding introduced by smoking in traditional observational studies. Materials and Methods: We used Mendelian randomization (MR) to screen 207 metabolites for their role in lung cancer predisposition using independent genome-wide association studies (GWAS) of blood metabolite levels (n = 7,824) and lung cancer risk (n = 29,266 cases/56,450 controls). A nested case-control study (656 cases and 1,296 matched controls) was subsequently performed using prediagnostic blood samples to validate MR association with lung cancer incidence data from population-based cohorts (EPIC and NSHDS). Results: An MR-based scan of 207 circulating metabolites for lung cancer risk identified that blood isovalerylcarnitine (IVC) was associated with a decreased odds of lung cancer after accounting for multiple testing (log10-OR = 0.43; 95% CI, 0.29-0.63). Molar measurement of IVC in prediagnostic blood found similar results (log10-OR = 0.39; 95% CI, 0.21-0.72). Results were consistent across lung cancer subtypes. Conclusions: Independent lines of evidence support an inverse association of elevated circulating IVC with lung cancer risk through a novel methodologic approach that integrates genetic and traditional epidemiology to efficiently identify novel cancer biomarkers. Impact: Our results find compelling evidence in favor of a protective role for a circulating metabolite, IVC, in lung cancer etiology. From the treatment of a Mendelian disease, isovaleric acidemia, we know that circulating IVC is modifiable through a restricted protein diet or glycine and L-carnatine supplementation. IVC may represent a modifiable and inversely associated biomarker for lung cancer. [ABSTRACT FROM AUTHOR]

Background: Though germline TP53 pathogenic/likely pathogenic variants (PV) are associated with Li-Fraumeni syndrome, many detected by multigene panels represent aberrant clonal expansion (ACE), most due to clonal hematopoiesis (CH). Discerning ACE/CH from germline variants and postzygotic mosaicism (PZM) is critically needed for risk assessment and management. Methods: Participants in the Li-Fraumeni & TP53 Understanding & Progress (LiFT UP) study with a TP53 PV were eligible. Demographics, personal/family cancer history, and clinical laboratory test reports were obtained. DNA from multiple tissues was analyzed using a custom QIAseq assay (ACE panel) that included TP53 and other CH-associated genes; the ACE panel and eyebrow follicles were assessed in a workflow to discern TP53 PV clinical categories. Results: Among 134 participants there was a significant difference for the age at diagnosis (P < 0.001), component cancers (P = 0.007), and clinical testing criteria (P < 0.001), comparing germline with PZM or ACE. ACE panel analysis of DNA from 55 sets of eyebrow follicles (mean 1.4 ug) and 36 formalin-fixed, paraffin imbedded tissues demonstrated low variance (SE, 3%; P = 0.993) for TP53 variant allele fraction, with no significant difference (P = 0.965) between tissue types, and detected CH gene PVs. Of 55 multi-tissue cases, germline status was confirmed for 20, PZM in seven, ACE for 25, and three were indeterminate. Additional CH variants were detected in six ACE and two germline cases. Conclusions: We demonstrated an effective approach and tools for discerning germline TP53 status. Impact: Discernment of PZM and TP53-driven CH increases diagnostic accuracy and enables risk-appropriate care. [ABSTRACT FROM AUTHOR]

Background: Prior genome-wide association studies have identified numerous lung cancer risk loci and reveal substantial etiologic heterogeneity across histologic subtypes. Analyzing the shared genetic architecture underlying variation in complex traits can elucidate common genetic etiologies across phenotypes. Exploring pairwise genetic correlations between lung cancer and other polygenic traits can reveal the common genetic etiology of correlated phenotypes. Methods: Using cross-trait linkage disequilibrium score regression, we estimated the pairwise genetic correlation and heritability between lung cancer and multiple traits using publicly available summary statistics. Identified genetic relationships were also examined after excluding genomic regions known to be associated with smoking behaviors, a major risk factor for lung cancer. Results: We observed several traits showing moderate single nucleotide polymorphism-based heritability and significant genetic correlations with lung cancer. We observed highly significant correlations between the genetic architectures of lung cancer and emphysema/chronic bronchitis across all histologic subtypes, as well as among lung cancer occurring among smokers. Our analyses revealed highly significant positive correlations between lung cancer and paternal history of lung cancer. We also observed a strong negative correlation with parental longevity. We observed consistent directions in genetic patterns after excluding genomic regions associated with smoking behaviors. Conclusions: This study identifies numerous phenotypic traits that share genomic architecture with lung carcinogenesis and are not fully accounted for by known smoking-associated genomic loci. [ABSTRACT FROM AUTHOR]

Background: The smoking behavior of American Indians (AI) differs from that of non-Hispanic whites (NHW). Typically light smokers, cessation interventions in AIs are generally less effective. To develop more effective cessation programs for AIs, clinicians, researchers, and public health workers need a better understanding of the genetic factors involved in their smoking behavior. Our aim was to assess whether SNPs associated with smoking behavior in NHWs are also associated with smoking in AIs. Methods: We collected questionnaire data on smoking behaviors and analyzed blood and saliva samples from two Tribal populations with dramatically different cultures and smoking prevalence, one in the Northern Plains (n = 323) and the other in the Southwest (n = 176). A total of 384 SNPs were genotyped using an Illumina custom GoldenGate platform. Samples were also assessed for cotinine and 3-hydroxycotinine as markers of nicotine intake and nicotine metabolite ratio. Results: Among 499 participants, we identified, in the Northern Plains sample only, a variant of the gamma-aminobutyric acid receptor subunit alpha-2 (GABRA2) (rs2119767) on chromosome 4p that was associated with many of the intake biomarkers of smoking we examined, suggesting a role for this gene in modifying smoking behavior in this population. We also identified three SNPs, in the Southwest sample only, as significant correlates of only cigarettes per day: rs4274224, rs4245147 (both dopamine receptor D2 gene), and rs1386493 (tryptophan hydroxylase 2 gene). Conclusions: The contribution of many genes known to underlie smoking behaviors in NHWs may differ in AIs. [ABSTRACT FROM AUTHOR]

Background: Lung cancer remains the leading cause of cancer death worldwide, with 15% to 20% occurring in never smokers. To assess genetic determinants for prognosis among never smokers, we conducted a genome-wide investigation in the International Lung Cancer Consortium (ILCCO). Methods: Genomic and clinical data from 1,569 never-smoking patients with lung cancer of European ancestry from 10 ILCCO studies were included. HRs and 95% confidence intervals of overall survival were estimated. We assessed whether the associations were mediated through mRNA expression-based 1,553 normal lung tissues from the lung expression quantitative trait loci (eQTL) dataset and Genotype-Tissue Expression (GTEx). For cross-ethnicity generalization, we assessed the associations in a Japanese study (N = 887). Results: One locus at 13q22.2 was associated with lung adenocarcinoma survival at genome-wide level, with carriers of rs12875562-T allele exhibiting poor prognosis [HR = 1.71 (1.41-2.07), P = 3.60 × 10-8], and altered mRNA expression of LMO7DN in lung tissue (GTEx, P = 9.40 × 10-7; Lung eQTL dataset, P = 0.003). Furthermore, 2 of 11 independent loci that reached the suggestive significance level (P < 10-6) were significant eQTL affecting mRNA expression of nearby genes in lung tissues, including CAPZB at 1p36.13 and UBAC1 at 9q34.3. One locus encoding NWD2/KIAA1239 at 4p14 showed associations in both European [HR = 0.50 (0.38-0.66), P = 6.92 × 10-7] and Japanese populations [HR = 0.79 (0.67-0.94), P = 0.007]. Conclusions: Based on the largest genomic investigation on the lung cancer prognosis of never smokers to date, we observed that lung cancer prognosis is affected by inherited genetic variants. Impact: We identified one locus near LMO7DN at genome-wide level and several potential prognostic genes with cis-effect on mRNA expression. Further functional genomics work is required to understand their role in tumor progression. [ABSTRACT FROM AUTHOR]

Background: Lung cancer kills more people than any other cancer in the United States. In addition to environmental factors, lung cancer has genetic risk factors as well, though the genetic etiology is still not well understood. We have performed whole exome sequencing on 262 individuals from 28 extended families with a family history of lung cancer. Methods: Parametric genetic linkage analysis was performed on these samples using two distinct analyses--the lung cancer only (LCO) analysis, where only patients with lung cancer were coded as affected, and the all aggregated cancers (AAC) analysis, where other cancers seen in the pedigree were coded as affected. Results: The AAC analysis yielded a genome-wide significant result at rs61943670 in POLR3B at 12q23.3. POLR3B has been implicated somatically in lung cancer, but this germline finding is novel and is a significant expression quantitative trait locus in lung tissue. Interesting genome-wide suggestive haplotypes were also found within individual families, particularly near SSPO at 7p36.1 in one family and a large linked haplotype spanning 4q21.3-28.3 in a different family. The 4q haplotype contains potential causal rare variants in DSPP at 4q22.1 and PTPN13 at 4q21.3. Conclusions: Regions on 12q, 7p, and 4q are linked to increased cancer risk in highly aggregated lung cancer families, 12q across families and 7p and 4q within a single family. POLR3B, SSPO, DSPP, and PTPN13 are currently the best candidate genes. [ABSTRACT FROM AUTHOR]

Background: Identifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans. Methods: We conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status. Results: We identified three novel genomic regions significantly associated (FDR-corrected P <0.10) with lung cancer risk (rs336958 on 5q14.3, rs7186207 on 16q22.2, and rs11658063 on 17q12). On chromosome16q22.2, rs7186207 was significantly associated with reduced risk [OR = 0.43; 95% confidence interval (CI), 0.73-0.89], and functional annotation using GTEx showed rs7186207 modifies DHODH gene expression. The minor allele at rs336958 on 5q14.3 was associated with increased lung cancer risk (OR = 1.47; 95% CI, 1.22-1.78), whereas the minor allele at rs11658063 on 17q12 was associated with reduced risk (OR = 0.80; 95% CI, 0.72-0.90). Conclusions: We identified novel associations on chromosomes 5q14.3, 16q22.2, and 17q12, which contain HNF1B, DHODH, and HAPLN1 genes, respectively. SNPs within these regions have been previously associated with multiple cancers. This is the first study to examine cross-cancer pleiotropic associations for lung cancer in African Americans. Impact: Our findings demonstrate novel cross-cancer pleiotropic associations with lung cancer risk in African Americans. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is associated with the highest mortality rate of all cancer types, and the most common histologic subtype of lung cancer is adenocarcinoma. To apply more effective therapeutic treatment, molecular markers that are able to predict the recurrence risk of patients with adenocarcinoma are critically needed. Mutations in TP53 tumor suppressor gene have been found in approximately 50% of lung adenocarcinoma cases, but the presence of a TP53 mutation does not always associate with increased mortality. Methods: The Cancer Genome Atlas RNA sequencing data of lung adenocarcinoma were used to define a novel gene signature for P53 deficiency. This signature was then used to calculate a sample-specific P53 deficiency score based on a patient's transcriptomic profile and tested in four independent lung adenocarcinoma microarray datasets. Results: In all datasets, P53 deficiency score was a significant predictor for recurrence-free survival where high P53 deficiency score was associated with poor survival. The score was prognostic even after adjusting for several key clinical variables including age, tumor stage, smoking status, and P53 mutation status. Furthermore, the score was able to predict recurrence-free survival in patients with stage I adenocarcinoma and was also associated with smoking status. Conclusions: The P53 deficiency score was a better predictor of recurrence-free survival compared with P53 mutation status and provided additional prognostic values to established clinical factors. Impact: The P53 deficiency score can be used to stratify early-stage patients into subgroups based on their risk of recurrence for aiding physicians to decide personalized therapeutic treatment. [ABSTRACT FROM AUTHOR]

Background: Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies. Methods: In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits. Results: After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (P < 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55, P = 0.003), lung and colorectal cancer (rg = 0.31, P = 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27, P = 0.009), and colorectal and breast cancer (rg = 0.22, P = 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected P value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41, P = 1.03 × 10-6). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer. Conclusions: Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors. Impact: This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis. [ABSTRACT FROM AUTHOR]

A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. [ABSTRACT FROM AUTHOR]

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. [ABSTRACT FROM AUTHOR]

Background: Although genome-wide association studies (GWAS) have identified many genetic variants that are strongly associated with lung cancer, these variants have low penetrance and serve as poor predictors of lung cancer in individuals. We sought to increase the predictive value of germline variants by considering their cumulative effects in the context of biologic pathways. Methods: For individuals in the Environment and Genetics in Lung Cancer Etiology study (1,815 cases/1,971 controls), we computed pathway-level susceptibility effects as the sum of relevant SNP variant alleles weighted by their log-additive effects from a separate lung cancer GWAS meta-analysis (7,766 cases/37,482 controls). Logistic regression models based on age, sex, smoking, genetic variants, and principal components of pathway effects and pathway-smoking interactions were trained and optimized in cross-validation and further tested on an independent dataset (556 cases/830 controls). We assessed prediction performance using area under the receiver operating characteristic curve (AUC). Results: Compared with typical binomial prediction models that have epidemiologic predictors (AUC = 0.607) in addition to top GWAS variants (AUC = 0.617), our pathway-based smokinginteractive multinomial model significantly improved prediction performance in external validation (AUC = 0.656, P < 0.0001). Conclusions: Our biologically informed approach demonstrated a larger increase in AUC over nongenetic counterpart models relative to previous approaches that incorporate variants. Impact: This model is the first of its kind to evaluate lung cancer prediction using subtype-stratified genetic effects organized into pathways and interacted with smoking. We propose pathway-exposure interactions as a potentially powerful new contributor to risk inference. [ABSTRACT FROM AUTHOR]

Background: DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility. Methods: We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling. Results: We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10-6), MSH5 (P < 5.09 × 10-6), and BRCA2 (P = 5.70 × 10-6). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways. Conclusions: Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways. Impact: Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria [ABSTRACT FROM AUTHOR]

Background: The Notch signaling pathway is constitutively activated in human cutaneous melanoma to promote growth and aggressive metastatic potential of primary melanoma cells. Therefore, genetic variants in Notch pathway genes may affect the prognosis of cutaneous melanoma patients. Methods: We identified 6,256 SNPs in 48 Notch genes in 858 cutaneous melanoma patients included in a previously published cutaneous melanoma genome-wide association study dataset. Multivariate and stepwise Cox proportional hazards regression and false-positive report probability corrections were performed to evaluate associations between putative functional SNPs and cutaneous melanoma disease-specific survival. Receiver operating characteristic curve was constructed, and area under the curve was used to assess the classification performance of the model. Results: Four putative functional SNPs of Notch pathway genes had independent and joint predictive roles in survival of cutaneous melanoma patients. The most significant variant was NCOR2 rs2342924 T>C (adjusted HR, 2.71; 95% confidence interval, 1.73-4.23; Ptrend = 9.62 × 10-7), followed by NCSTN rs1124379 G>A, NCOR2 rs10846684 G>A, and MAML2 rs7953425 G>A (Ptrend = 0.005, 0.005, and 0.013, respectively). The receiver operating characteristic analysis revealed that area under the curve was significantly increased after adding the combined unfavorable genotype score to the model containing the known clinicopathologic factors. Conclusions: Our results suggest that SNPs in Notch pathway genes may be predictors of cutaneous melanoma disease-specific survival. Impact: Our discovery offers a translational potential for using genetic variants in Notch pathway genes as a genotype score of biomarkers for developing an improved prognostic assessment and personalized management of cutaneous melanoma patients. [ABSTRACT FROM AUTHOR]

The article presents a research that examines association of single-nucleotide polymorphisms (SNP) in MircoRNA (miRNA) sequence and non-small cell lung cancer (NSCLC) survival. The study used data from a genome-wide association study (GWAS) in a Caucasian population from the Massachusetts General Hospital in Boston, Massachusetts, to analysis of associations of 142 miRNA SNPs with non-small cell lung cancer (NSCLC) survival. The result showed association of miRNA SNPs with NSCLC survival.

The article presents the study which examined the relationship between 238 single-nucleotide polymorphisms (SNP) in 26 angiogenesis and lymphangiogenesis genes in the progression of melanoma and the risk of sentinel lymph node (SLN) metastasis and mortality. Also cited are the common prognostic features of melanoma including tumor thickness, ulceration, and mitotic rate. The study examined data provided by the Moffitt Cancer Center in Tampa, Florida.

The article discusses a study which investigated lung cancer susceptibility loci in African Americans using reduced linkage disequilibrium. Logistic regression was used to estimate associations between polymorphisms and lung cancer risk. It identifies polymorphisms that are associated with lung cancer in African Americans and which variants are risk factors for adenocarcinoma and for squamous cell carcinoma.