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Top genotyped SNP associations with metastasis at diagnosis in the discovery and all replication studies.

Top 30 loci associated with metastasis at diagnosis in the discovery set of 541 European osteosarcoma cases.

Relationship of variables to metastasis at diagnosis in the discovery set.

SNPs in the NFIB locus associated with metastasis at diagnosis with P{less than or equal to}1x10-5 in the discovery stage, and functionally annotated with information from the ENCODE and 1000 Genomes Project data.

Associations of the top GWAS and imputed SNP with metastasis at diagnosis in the discovery stage (European ancestry) by inheritance model.

Supplementary Figure 1. Manhattan plot of the Discovery stage. SNPs in the NFIB risk locus are highlighted in green. Supplementary Figure 2. LD structure of the NFIB risk locus. Plot was made using the CEU population of the 1000 Genomes Project data with LDlink (ref 54). Supplementary Figure 3. Significant relationship between the genotype of the metastasis associated SNP rs7034162, and expression of NFIB and IGFBP5 in osteosarcoma cell lines and tumors. Significance is based on linear regression comparing the distribution of expression of NFIBbetween the TT homozygous non-risk genotype (combined N=34) of rs7034162 genotypes to the heterozygous risk AT (combined N=10) and the homozygous risk AA genotypes (combined N=2). The green triangle represents the expression levels in the OSA cell line, the blue circle is expression levels in the HOS cell line, and the red square the U2OS cell line expression. These analyses were based on the publically available genotype and expression data from 17 osteosarcoma cell lines and 29 osteosarcoma tumors (ref 20). Supplementary Figure 4. No significant relationship between the genotype of the metastasis associated SNP, rs7034162, and expression of protein-encoding genes FREM1, ZDHHC1, and MPDZ in the neighborhood of NFIB in osteosarcoma cell lines and tumors. Significance is based on linear regression comparing the distribution of expression of FREM1, ZDHHC1, and MPDZ between the TT homozygous non-risk genotype (combined N=34) of rs7034162 genotypes to the heterozygous risk AT (combined N=10) and the homozygous risk AA genotypes (combined N=2). The green triangle represents the expression levels in the OSA cell line, the blue circle is expression levels in the HOS cell line, and the red square the U2OS cell line expression. These analyses were based on the publically available genotype and expression data from 17 osteosarcoma cell lines and 29 osteosarcoma tumors (ref 20). Supplementary Figure 5. The human osteosarcoma cell lines, U2OS and HOS, had higher NFIB protein levels then OSA cells. NFIB levels were determined using immunoblot analysis in the OSA, HOS and U2OS cells both basal (A) and after treatment with siRNA against NFIB (B). Supplementary Figure 6. NFIB expression significantly correlates with IGFBP5 expression in osteosarcoma cell lines and tumors. Significance is based on linear regression comparing the expression levels of NFIB with the corresponding IGFBP5 expression levels. Supplementary Figure 7. Expression levels of IGFBP5 decreases after NFIB suppression of human osteosarcoma cell lines. IGFBP5 expression of OSA, HOS and U2OS cells was determined 48 hours after transfection with control siRNA (si-NEG) or siRNA targeting NFIB (si-NFIB). Graph showing relative expression compared to control treated U2OS cells. Supplementary Figure 8. A model of how the NFIB risk locus leads to changes in NFIB expression and potentially may affect osteosarcoma metastatic potential. The risk allele (right panel) leads to lowered expression of NFIB and NFIB-mediated lower expression of IGFPB5, which then leads to less IGFBP5-mediated inhibition of IGF-1 (right panel, grey arrows), leading to an increase in proliferation, survival and metastasis of osteosarcoma cells (right panel, black arrows). The reference allele (left panel) leads to both higher expression of NFIB and higher expression of NFIB-mediated IGFPB5. In turn, higher IGFBP5 levels leads to increased inhibition of IGF-1 (left panel, black arrows), leading to a decrease in proliferation, survival and metastasis of osteosarcoma cells (left panel, grey arrows). Supplementary Figure 9. Plot of the PCA Eigenvectors of the Discovery stage. Supplementary Figure 10. QQ-plot of the Discovery stage.

Description of participating case studies.

The oral microbiome, like the fecal microbiome, may be related to breast cancer risk. Therefore, we investigated whether the oral microbiome was associated with breast cancer and nonmalignant breast disease, and its relationship with the fecal microbiome in a case-control study in Ghana. A total of 881 women were included (369 breast cancers, 93 nonmalignant cases and 419 population-based controls). The V4 region of the 16S rRNA gene was sequenced from oral and fecal samples. Alpha-diversity (observed amplicon sequence variants [ASVs], Shannon index and Faith's Phylogenetic Diversity) and beta-diversity (Bray-Curtis, Jaccard and weighted and unweighted UniFrac) metrics were computed. MiRKAT and logistic regression models were used to investigate the case-control associations. Oral sample alpha-diversity was inversely associated with breast cancer and nonmalignant breast disease with odds ratios (95% CIs) per every 10 observed ASVs of 0.86 (0.83-0.89) and 0.79 (0.73-0.85), respectively, compared to controls. Beta-diversity was also associated with breast cancer and nonmalignant breast disease compared to controls (P ≤ .001). The relative abundances of Porphyromonas and Fusobacterium were lower for breast cancer cases compared to controls. Alpha-diversity and presence/relative abundance of specific genera from the oral and fecal microbiome were strongly correlated among breast cancer cases, but weakly correlated among controls. Particularly, the relative abundance of oral Porphyromonas was strongly, inversely correlated with fecal Bacteroides among breast cancer cases (r = -.37, P ≤ .001). Many oral microbial metrics were strongly associated with breast cancer and nonmalignant breast disease, and strongly correlated with fecal microbiome among breast cancer cases, but not controls.

Supplementary Methods and Tables

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. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

Background Few studies have evaluated the relationship between CDKN2A germline pathogenic variants (GPV), transcript (p16/p14ARF) alteration, and cancer risk. Methods Standardized incidence ratios (SIRs) comparing cancer risk with the general population were calculated for 385 CDKN2A GPV carriers from 2 large cohorts (259 United States and 126 Swedish individuals) using Poisson regression; statistical significance was defined as P less than .002 (Bonferroni correction). Cumulative incidence is reported for melanoma and nonmelanoma cancer. Results Incidence was increased for melanoma (SIR = 159.8, 95% confidence interval [CI] = 132.1 to 193.2), pancreatic cancer (SIR = 24.1, 95% CI = 14.7 to 39.4), head and neck squamous cell carcinoma (SIR = 16.2, 95% CI = 9.5 to 27.6), and lung cancer (SIR = 5.6, 95% CI = 3.4 to 9.1) in GPV carriers. Similar associations were observed with p16 alteration. Combined p16 and p14ARF alteration was associated with increased incidence of esophageal cancer (SIR = 16.7, 95% CI = 5.7 to 48.9) and malignant peripheral nerve sheath tumor (SIR = 113.0, 95% CI = 16.4 to 780.9), although cancer events were limited (n Conclusion These findings highlight the impact of p16 and p14ARF alteration on cancer risk. Smoking was an important risk factor for smoking-related cancers in our study.

This nested case-control study in the NIH-AARP Diet and Health Study was carried out to prospectively investigate the relationship of oral microbiome with head and neck cancer (HNC).56 incident HNC cases were identified, and 112 controls were incidence-density matched to cases. DNA extracted from pre-diagnostic oral wash samples was whole-genome shotgun metagenomic sequenced to measure the overall oral microbiome. ITS2 gene qPCR was used to measure the presence of fungi. ITS2 gene sequencing was performed on ITS2 gene qPCR positive samples. We computed taxonomic and functional alpha-diversity and beta-diversity metrics. The presence and relative abundance of groups of red-complex (e.g., Porphyromonas gingivalis) and/or orange-complex (e.g., Fusobacterium nucleatum) periodontal pathogens were compared between cases and controls using conditional logistic regression models and MiRKAT.Participants with higher taxonomic microbial alpha-diversity had a non-statistically significant decreased risk of HNC. No case-control differences were found for beta diversity by MiRKAT model (all p 0.05). A greater relative abundance of red-complex periodontal pathogens (OR = 0.51, 95 % CI = 0.26-1.00), orange-complex (OR = 0.38, 95 % CI = 0.18-0.83), and both complexes' pathogens (OR = 0.32, 95 % CI = 0.14-0.75), were associated with reduced risk of HNC. The presence of oral fungi was also strongly associated with reduced risk of HNC compared with controls (OR = 0.39, 95 % CI = 0.17-0.92).Greater taxonomic alpha-diversity, the presence of oral fungi, and the presence or relative abundance of multiple microbial species, including the red- and orange-complex periodontal pathogens, were associated with reduced risk of HNC. Future studies with larger sample sizes are needed to evaluate these associations.

Oral bacteria play important roles in human health and disease. Oral samples collected using ethanol-containing mouthwash are widely used for oral microbiome studies. However, ethanol is flammable and not ideal for transportation/storage in large quantities, and some individuals may avoid ethanol due to the burning sensation or due to various personal, medical, religious, and/or cultural factors. Here, we compared ethanol-free and ethanol-containing mouthwashes using multiple microbiome metrics and assessed the stability of the mouthwash samples stored up to 10 days before processing. Forty volunteers provided oral wash samples collected using ethanol-free and ethanol-containing mouthwashes. From each sample, one aliquot was immediately frozen, one was stored at 4°C for 5 days and frozen, while the third aliquot was stored for 5 days at 4°C and 5 days at ambient temperature to mimic shipping delays and then frozen. DNA was extracted, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatic processing was performed using QIIME 2. Microbiome metrics measured in the two mouthwash types were very similar, with intraclass correlation coefficients (ICCs) for alpha and beta diversity metrics greater than 0.85. Relative abundances of some taxa were significantly different, but ICCs of the top four most abundant phyla and genera were high (> 0.75) for the comparability of the mouthwashes. Stability during delayed processing was also high for both mouthwashes based on alpha and beta diversity measures and relative abundances of the top four phyla and genera (ICCs ≥ 0.90). These results demonstrate ethanol-free mouthwash performs similarly to ethanol-containing mouthwash for microbial analyses, and both mouthwashes are stable for at least 10 days without freezing prior to laboratory processing. Ethanol-free mouthwash is suitable for collecting and shipping oral wash samples, and these results have important implications for planning future epidemiologic studies of the oral microbiome.

Background Previous studies suggested associations between the oral microbiome and lung cancer, but studies were predominantly cross-sectional and underpowered. Methods Using a case-cohort design, 1306 incident lung cancer cases were identified in the Agricultural Health Study; National Institutes of Health-AARP Diet and Health Study; and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Referent subcohorts were randomly selected by strata of age, sex, and smoking history. DNA was extracted from oral wash specimens using the DSP DNA Virus Pathogen kit, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatics were conducted using QIIME 2. Hazard ratios and 95% confidence intervals were calculated using weighted Cox proportional hazards models. Results Higher alpha diversity was associated with lower lung cancer risk (Shannon index hazard ratio = 0.90, 95% confidence interval = 0.84 to 0.96). Specific principal component vectors of the microbial communities were also statistically significantly associated with lung cancer risk. After multiple testing adjustment, greater relative abundance of 3 genera and presence of 1 genus were associated with greater lung cancer risk, whereas presence of 3 genera were associated with lower risk. For example, every SD increase in Streptococcus abundance was associated with 1.14 times the risk of lung cancer (95% confidence interval = 1.06 to 1.22). Associations were strongest among squamous cell carcinoma cases and former smokers. Conclusions Multiple oral microbial measures were prospectively associated with lung cancer risk in 3 US cohort studies, with associations varying by smoking history and histologic subtype. The oral microbiome may offer new opportunities for lung cancer prevention.

Background: Risk estimates for women carrying germline mutations in breast cancer susceptibility genes are mainly based on studies of European ancestry women. Methods: We investigated associations between pathogenic variants (PV) in 34 genes with breast cancer risk in 871 cases [307 estrogen receptor (ER)-positive, 321 ER-negative, and 243 ER-unknown] and 1,563 controls in the Ghana Breast Health Study (GBHS), and estimated lifetime risk for carriers. We compared results with those for European, Asian, and African American ancestry women. Results: The frequency of PV in GBHS for nine breast cancer genes was 8.38% in cases and 1.22% in controls. Relative risk estimates for overall breast cancer were: (OR, 13.70; 95% confidence interval (CI), 4.03–46.51) for BRCA1, (OR, 7.02; 95% CI, 3.17–15.54) for BRCA2, (OR, 17.25; 95% CI, 2.15–138.13) for PALB2, 5 cases and no controls carried TP53 PVs, and 2.10, (0.72–6.14) for moderate-risk genes combined (ATM, BARD1, CHEK2, RAD51C, RAD52D). These estimates were similar to those previously reported in other populations and were modified by ER status. No other genes evaluated had mutations associated at P < 0.05 with overall risk. The estimated lifetime risks for mutation carriers in BRCA1, BRCA2, and PALB2 and moderate-risk genes were 18.4%, 9.8%, 22.4%, and 3.1%, respectively, markedly lower than in Western populations with higher baseline risks. Conclusions: We confirmed associations between PV and breast cancer risk in Ghanaian women and provide absolute risk estimates that could inform counseling in Ghana and other West African countries. Impact: These findings have direct relevance for breast cancer genetic counseling for women in West Africa.

Telomere length (TL) and DNA methylation–based epigenetic clocks are markers of biological age, but the relationship between the two is not fully understood. Here, we used multivariable regression models to evaluate the relationships between leukocyte TL (LTL; measured by qPCR [n = 635] or flow FISH [n = 144]) and five epigenetic clocks (Hannum, DNAmAge pan-tissue, PhenoAge, SkinBlood, or GrimAge clocks), or their epigenetic age acceleration measures in healthy adults (age 19–61 years). LTL showed statistically significant negative correlations with all clocks (qPCR: r = − 0.26 to − 0.32; flow FISH: r = − 0.34 to − 0.49; p 0.05 for both). In conclusion, the relationships between LTL and epigenetic clocks were limited to clocks reflecting phenotypic age. The observed association between LTL and EEAA reflects the ability of both measures to detect immunosenescence. The observed modest correlations between LTL and epigenetic clocks highlight a possible benefit from incorporating both measures in understanding disease etiology and prognosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11357-022-00586-4.

Background Pediatric cancers are the leading cause of death by disease in children despite improved survival rates overall. The contribution of germline genetic susceptibility to pediatric cancer survivors has not been extensively characterized. We assessed the frequency of pathogenic or likely pathogenic (P/LP) variants in 5451 long-term pediatric cancer survivors from the Childhood Cancer Survivor Study. Methods Exome sequencing was conducted on germline DNA from 5451 pediatric cancer survivors (cases who survived ≥5 years from diagnosis; n = 5105 European) and 597 European cancer-free adults (controls). Analyses focused on comparing the frequency of rare P/LP variants in 237 cancer-susceptibility genes and a subset of 60 autosomal dominant high-to-moderate penetrance genes, for both case-case and case-control comparisons. Results Of European cases, 4.1% harbored a P/LP variant in high-to-moderate penetrance autosomal dominant genes compared with 1.3% in controls (2-sided P = 3 × 10-4). The highest frequency of P/LP variants was in genes typically associated with adult onset rather than pediatric cancers, including BRCA1/2, FH, PALB2, PMS2, and CDKN2A. A statistically significant excess of P/LP variants, after correction for multiple tests, was detected in patients with central nervous system cancers (NF1, SUFU, TSC1, PTCH2), Wilms tumor (WT1, REST), non-Hodgkin lymphoma (PMS2), and soft tissue sarcomas (SDHB, DICER1, TP53, ERCC4, FGFR3) compared with other pediatric cancers. Conclusion In long-term pediatric cancer survivors, we identified P/LP variants in cancer-susceptibility genes not previously associated with pediatric cancer as well as confirmed known associations. Further characterization of variants in these genes in pediatric cancer will be important to provide optimal genetic counseling for patients and their families.

Objective: This nested case-control study in the NIH-AARP Diet and Health Study was carried out to prospectively investigate the relationship of oral microbiome with head and neck cancer. Methods: Among 34,262 participants with oral wash samples, 60 incident head and neck cancer cases were identified during a mean of 6.25±1.28 years of follow-up. Two controls were matched to each case by age at sample collection, sex, and baseline smoking history, and available controls were not diagnosed with head and neck cancer over follow-up. Whole genome shotgun metagenomic sequencing was used to measure the overall oral microbiome, and ITS2 gene qPCR was used to measure the presence of fungi in pre-diagnostic oral wash samples. ITS2 gene sequencing was performed on ITS2 qPCR positive samples. Taxonomic and functional alpha-diversity and beta-diversity metrics were computed. Presence/absence and relative abundance of groups of red- and/or orange-complex periodontal pathogens were also calculated. Conditional logistic regression models and MiRKAT were used to investigate the case-control associations. Results: Participants with higher taxonomic microbial alpha-diversity had a decreased risk of head and neck cancer with odds ratios per every 10 observed species of 0.87 (95% CI=0.75-1.004, P=0.057), and per one unit of Faith’s PD and the Shannon index of 0.84 (95% CI=0.72-0.99, P=0.032) and 0.52 (95% CI=0.29-0.94, P=0.032), respectively. No case-control differences were found for beta diversity (all p>0.05). The presence of red-complex periodontal pathogens was non-significantly associated with reduced risk of head and neck cancer (OR=0.41, 95% CI=0.17-1.01, P=0.052). Greater relative abundance of red-complex (OR=0.29, 95% CI=0.09-0.94, P=0.040), orange-complex (OR=0.45, 95% CI=0.22-0.89, P=0.022), and both complexes combined (OR=0.46, 95% CI=0.25-0.82, P=0.009), were associated with reduced risk of head and neck cancer. The presence of oral fungi was also strongly associated with reduced risk of head and neck cancer compared with controls (OR=0.39, 95% CI=0.17-0.87, P=0.022). Conclusions: Greater taxonomic alpha-diversity and the presence or relative abundance of multiple bacterial or fungal species, including the red- and orange-complex periodontal pathogens, were associated with reduced risk of head and neck cancer. Citation Format: Zeni Wu, Yongli Han, Yunhu Wan, Xing Hua, Casey L. Dagnall, Kristine Jones, Amy Hutchinson, Belynda D. Hicks, Weiyin Zhou, Linda Liao, Heather Hallen-Adams, Jianxin Shi, Christian C. Abnet, Rashmi Sinha, Anil Chaturvedi, Emily Vogtmann. The oral microbiome and the risk of head and neck cancer: A nested case-control study in the NIH-AARP [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 687.

Following the Chernobyl nuclear power plant explosion in Ukraine in 1986, increased childhood exposure to radioactive iodine (131I), which occurred primarily through contaminated food sources, has been consistently associated with increased risk of developing papillary thyroid carcinoma (PTC). Increased frequency of cervical lymph node metastases (LNM) is well recognized in pediatric PTC, including pediatric cases following the Chernobyl accident. We recently leveraged the collection of fresh-frozen tumor tissues from the Chernobyl Tissue Bank to conduct a genomic landscape analysis of 440 cases of PTC that provided new insights into radiation-related molecular characteristics of PTC occurring after the accident (Morton et al., Science 2021). Here, we extend that study to conduct a genomic landscape analysis of LNMs for a subset of 48 PTC cases to investigate the specific genomic alterations occurring in LNM. The analysis set comprised 144 samples, including fresh-frozen treatment-naïve primary and LNM PTC tumor samples as well as matched normal tissue or blood. Overall, the mutational load was highly concordant between primary and metastatic PTC. On average, 50% of somatic single nucleotide variants and 97% structural variants were shared between primary and metastatic PTCs. In contrast, the burden of somatic copy number alterations (SCNA) between primary tumor and LNM pairs was less concordant, particularly for copy number gains, whereas most of the copy number loss was found to be shared between matched pairs. PTC is usually driven by one driver mutation, most often involving the mitogen-activated protein kinase (MAPK) pathway. All driver mutations were shared between primary and metastatic PTC and were clonal; thus, no additional driver mutations were detected in metastatic PTC. Notably, however, the matched pairs in this study disproportionately had fusion drivers (77%), whereas only 23% of the drivers were BRAF V600E and none were RAS mutations. Transcriptome analysis revealed differentially expressed genes (DEGs) in metastatic PTC compared to primary PTC; three-quarters of the DEGs were overexpressed in metastatic PTC. Half of the LNM overexpressed DEGs were members of the HOXC family, which has been linked with epithelial-mesenchymal transition in cancer progression. There was also reduced expression in LNM for the DLX family, which relates to TGF-beta signaling. Our findings did not reveal a relationship between radiation dose and expression profiles in the LNM, comparable to our findings for the primary PTCs. We still observe that the efficiency of the radiation-induced PTC is paramount and subsequent events are directly related to the drivers in the MAPK pathway. For the cervical LNMs, we observed expression profiles not observed in the primary PTC that could give new insights into PTC local metastases. Citation Format: Olivia W. Lee, Danielle M. Karyadi, Chip Stewart, Tetiana I. Bogdanova, Jieqiong Dai, Stephen W. Hartley, Sara J. Schonfeld, Vidushi Kapoor, Marko Krznaric, Meredith Yeager, Amy Hutchinson, Belynda D. Hicks, Casey L. Dagnall, Julie M. Gastier-Foster, Jay Bowen, Mitchell J. Machiela, Elizabeth K. Cahoon, Kiyohiko Mabuchi, Vladimir Drozdovitch, Sergii Masiuk, Mykola Chepurny, Liudmyla Y. Zurnadzhy, Amy Berrington de González, Gad Getz, Gerry A. Thomas, Mykola D. Tronko, Lindsay M. Morton, Stephen J. Chanock. Genomic characterization of lymph node metastases in papillary thyroid carcinoma following the Chernobyl accident reveals an expression profile specific to metastatic process [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 980.