Cancer Epidemiology, Biomarkers & Prevention

This study examines changes in oral risk habits and identifies factors influencing these changes among participants in a population-based oral cancer screening program to support effective public health interventions. The study included 2,569,920 individuals aged 30 and older who participated in Taiwans Oral Cancer Screening Program at least twice between 2010 and 2021. Changes in cigarette smoking and betel quid chewing were assessed between the first and last screenings and categorized as improved, unchanged, or worsened. A logistic regression model evaluated factors associated with habit improvement, including baseline oral habits, sex, age, education, screening adherence, and oral potentially malignant disorder (OPMD) findings. Among participants, 25.3% improved their oral habits. Baseline habits influenced how OPMD screening results affected behavior change. Among smokers, a positive screening result increased the likelihood of quitting or reducing smoking (adjusted odds ratio [aOR] = 1.18, 95% CI 1.16-1.20). However, among betel quid chewers, whether or not they smoked, a positive screening result was negatively associated with improved habits (aOR 0.79-0.88). Being female, older, college-educated, and regularly attending screenings were positively linked to behavior improvement. The program led to habit improvements in about one-quarter of participants, particularly older individuals, those with higher education, and frequent attendees. However, a diagnosis of OPMD motivated change only among smokers, not those engaging in both smoking and betel quid chewing, highlighting a lack of awareness in high-risk groups. Strengthening collaboration between health organizations and the screening program could enhance public awareness, improve program effectiveness, reduce oral cancer incidence, and lower long-term healthcare costs.

Head and neck cancer (HNC) is the sixth most common cancer globally. Incidence and survival rates vary significantly across geographic regions and tumor subsites. This is partly due to differences in risk factor exposure, which includes tobacco smoking, alcohol consumption and human papillomavirus (HPV) infection, alongside detection and treatment strategies. The VOYAGER (human papillomaVirus, Oral and oropharYngeal cAncer GEnomic Research) consortium is a collaboration between five large North American and European studies which generated data on 10,530 participants (7,233 cases and 3,297 controls). The primary goal of the collaboration was to improve understanding of the role of HPV and genetic factors in oral cavity and oropharyngeal cancer risk and outcome. Demographic and clinical data collected by the five studies were harmonized, and HPV status was determined for the majority of cases. In addition, 999 tumors were sequenced to define somatic mutations. These activities generated a comprehensive biomedical resource that can be utilized to answer critical outstanding research questions to help improve HNC prevention, early detection, treatment, and surveillance.

BackgroundWe previously reported that >5% of the population carries pathogenic or likely pathogenic variants (P/LPVs) in key cancer susceptibility genes. However, gene-specific cancer prevalence, spectrum, burden, lifetime risk, comorbidity, and the risk associated with autosomal recessive (AR) genes among carriers remain incompletely defined. MethodsWe analyzed 72 cancer susceptibility genes in the All of Us dataset (N=633,547), including 287,076 participants with both genomic and electronic health record data. Cancer diagnoses were identified using SNOMED codes and grouped into 35 categories. Associations between P/LPVs and overall and site-specific cancer risk were evaluated using regression models adjusted for age, sex, race, and ethnicity. ResultsAmong genes with [≥]10 unique carriers, cancer prevalence was highest for MEN1 (80%), followed by TP53 (57.7%), MLH1 (48.4%), and MSH2 (47.2%). Carriers of P/LPVs in BRCA1, BRCA2, MLH1, APC, NF1, PTEN, and PALB2 had significantly earlier cancer diagnosis compared to non-carriers. Cancer prevalence was markedly higher in BRCA1 and BRCA2 carriers who are also mono-allelic MUTYH carriers (75% and 45.5%, respectively) compared with BRCA1 and BRCA2 alone (43.2% and 36.5%). Adjusted survival analysis showed increased cancer risk for MLH1 (OR=6.08), PTEN (OR=5.80), and MSH2 (OR=5.19). Novel associations included MITF with anal/perianal and prostate cancer; BLM with ovarian and soft tissue/sarcoma; WRN with gynecologic cancer (NOS); and FH with hematologic malignancy. ConclusionsThis population-based analysis defines gene-specific cancer prevalence, spectrum, and risk, including contributions from AR variants, in the U.S. population. These findings support more precise genetic testing, screening, and risk stratification for individuals carrying inherited P/LPVs.

BackgroundEpigenome-wide association studies (EWAS) using peripheral blood have identified specific sites of DNA methylation associated with risk of various cancers and may hold promise to identify novel biomarkers of risk; however, few studies have been performed for pancreatic cancer and none using a prospective study design. MethodsUsing a nested case-control study design, incident pancreatic cancer cases and matched controls were identified from participants who provided blood at baseline in three prospective cohort studies (Nurses Health Study, Health Professionals Follow-up Study and Physicians Health Study). DNA methylation levels were measured in DNA extracted from leukocytes using the Illumina MethylationEPIC array. Average follow-up period for this analysis was 13 years. ResultsA region in chromosome 16 near genesTMEM204 and IFT140 was identified as being differentially methylated in cases and controls. For some CpGs in the region, the associations were stronger with shorter time to diagnosis (e.g., OR= 5.95, 95% CI = 1.52-23.12, for top vs bottom quartile, for <5 years between blood draw and cancer diagnosis) but associations remained significantly higher even when cases were diagnosed over 10 years after blood collection. Statistically significant differences in DNA methylation levels were also observed in the gastric secretion pathway using GSEA analysis. ConclusionsChanges in DNA methylation in peripheral blood may mark alterations in metabolic or immune pathways (potentially including alterations in immune subtypes) that play a role in pancreatic cancer. Identifying new biological pathways in carcinogenesis of pancreatic cancer using EWAS approach could provide new opportunities for improving treatment and prevention.

Obesity is a leading risk factor for cancer, but whether obesity is linked to specific genomic subtypes of cancer is unknown. Here, we examined the relationship between obesity and tumor genotype in two large clinicogenomic corpora. Obesity was associated with specific driver mutations in lung adenocarcinoma, endometrial carcinoma, and cancers of unknown primary, independent of clinical covariates and genetic ancestry. Obesity is therefore a putative driver of etiologic heterogeneity across cancers.

BackgroundRed meat consumption is a risk factor for colorectal cancer (CRC) and has been linked to tumor alkylating DNA damage. rs16906252-T is a cis expression quantitative trait locus (eQTL) variant associated with silencing of MGMT, a central alkylating damage repair gene. We hypothesize that rs16906252-T carriers are predisposed to alkylating damage mutations. MethodsWe conducted mutational signature deconvolution of CRC whole-exome sequencing data from The Cancer Genome Atlas (TCGA, n = 540), the Nurses Health Studies/ Health Professional Follow-up Study (NHS/HPFS, n = 900) as well as non-western samples from the Pan-Cancer Analysis of Whole Genomes (COCA-CN, n = 295); and examined the relationship of rs16906252-T with putative alkylation-dependent tumor mutations. Leveraging lifestyle data from NHS/HPFS, we also investigated the interaction between red meat consumption and rs16906252-T. ResultsAmong CRC patients, rs16906252-T carriers exhibited higher tumor alkylating damage compared to non-carriers. In the general population, rs16906252-T is largely absent in individuals with East Asian ancestries, and we consistently find a negligible contribution of alkylating damage in CRC patients with East Asian ancestries. We show that the alkylating mutational signatures carcinogenicity is mainly mediated by KRAS G12D and G13D mutations. We also observe a synergistic effect of rs16906252-T with high pre-diagnosis red meat intake for tumor alkylating damage. ConclusionsMGMT rs16906252-T carriers are predisposed to CRC oncogenic alkylating damage which is potentiated by red meat intake. ImpactOur results support a causal relationship between red meat and CRC and can lead to tailored dietary and screening guidelines for CRC prevention.

Prostate cancer (PrCa) is one of the most genetically driven solid cancers with heritability estimates as high as 57%. African American men are at an increased risk of PrCa; however, current risk prediction models are based on European ancestry groups and may not be broadly applicable. In this study, we define an African ancestry group of 4,533 individuals to develop an African ancestry-specific PrCa polygenic risk score (PRState). We identified risk loci on chromosomes 3, 8, and 11 in the African ancestry group GWAS and constructed a polygenic risk score (PRS) from 10 African ancestry-specific PrCa risk SNPs, achieving an AUC of 0.61 [0.60-0.63] and 0.65 [0.64-0.67], when combined with age and family history. Performance dropped significantly when using ancestry-mismatched PRS models but remained comparable when using trans-ancestry models. Importantly, we validated the PRState score in the Million Veteran Program, demonstrating improved prediction of PrCa and metastatic PrCa in African American individuals. This study underscores the need for inclusion of individuals of African ancestry in gene variant discovery to optimize PRS.

BackgroundTobacco pouch keratosis (TPK) is a common oral mucosal lesion among smokeless tobacco users, with potential for malignant transformation. Despite its public health importance, pooled prevalence estimates for India remains limited. MethodsA comprehensive search will be conducted in PubMed, Embase, and Scopus, along with grey literature sources (Google Scholar and Shodhganga). Observational epidemiological studies published from 2000 onwards, reporting the prevalence of TPK in India, will be included. Forward and backward citation searches will also be performed. The study selection process will be documented using the PRISMA 2020 flow diagram. Data will be extracted using the Joanna Briggs Institute (JBI) standardized form, and methodological quality will be assessed using the JBI Critical Appraisal Checklist for prevalence studies. Key study characteristics and results will be tabulated, and provide a narrative synthesis. Pooled prevalence will be estimated using a random-effects model (restricted maximum likelihood method), with heterogeneity assessed via Cochrans Q and I2 statistics. If fewer than five studies are available, the Hartung- Knapp-Sidik-Jonkman method will be applied. Subgroup analyses will be performed by age group, gender, and study setting. Publication bias will be evaluated using funnel plots and Eggers test. The certainty of evidence will be graded using the GRADEpro framework. DiscussionThis review will generate pooled prevalence estimates of TPK across diverse populations and settings in India and will also provide evidence-based insights for researchers, clinicians, public health professionals, and policymakers involved in tobacco control and oral health initiatives. PROSPERO registrationCRD420251119683

PurposeMost research on genetic screening and precision oncology is based on participants of European ancestry, making it vital to evaluate the performance of these approaches in diverse populations. We analysed data from the 100,000 Genomes Project (100kGP) to assess ancestry-related differences in cancer variant prioritisation. Patients and MethodsTo assess the representativeness of the 14,775 participants with cancer from the 100kGP, we compared recruitment ratios for self-reported ethnicities to those in England. For genetic ancestry groups we analysed differences in detection rates for potential pathogenic variants (PVs) in the germline and somatic mutations in genes with treatment implications and investigated possible causes of observed disparities. ResultsRecruitment rates for Black and Asian ethnicities compared with White ethnicity in the 100kGP were consistent with rates in England, except for bladder and prostate (Black and Asian) and breast (Asian only) where Black and Asian ethnicities were recruited at higher rates than expected compared to White ethnicity. Patients with non-European genetic ancestry were more likely to carry variants classified as potential pathogenic compared to European ancestry (p=0.006). PVs were identified in 4.6% of South Asian (adjusted model: odds ratio=1.88, 95%CI=1.21-2.93) and 5.3% of African ancestry patients (odds ratio=2.24, 95%CI=1.44-3.48) compared with 2.2% in European. Fewer non-synonymous somatic mutations in actionable genes were identified in patients of non-European ancestry (p=0.004). WGS failed to identify treatment-relevant findings for 26% of patients of South Asian ancestry compared with 16% of European ancestry. ConclusionThe excess germline variants classified as PVs in patients with non-European ancestry may impede the diagnostic process. Our analysis demonstrates the need for better variant classification across diverse ancestries to ensure equitable implementation of genomics in cancer care.

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we conducted analyses of emulated trials for 11 drugs across 290 comparisons and identified three drugs significantly associated with reduced colorectal cancer risk: caffeine vs. paroxetine (HR, 0.51; 95% CI, 0.41-0.64), haloperidol vs. prochlorperazine (HR, 0.47; 95% CI, 0.33-0.68), and trazodone hydrochloride vs. paroxetine (HR, 0.49; 95% CI, 0.38-0.63). Conversely, caffeine was associated with increased cancer risk in comparisons with finasteride (colorectal cancer) and fluoxetine (breast cancer). Meta-analysis identified six drugs significantly associated with cancer risk, including acetazolamide, which was associated with reduced colorectal cancer risk (HR, 0.79; 95% CI, 0.72-0.87). This study identifies novel protein biomarkers and candidate drug targets across six major cancer types and highlights several approved drugs with potential chemopreventive effects.

BackgroundDEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate risk regions by considering the risk signals from over-lapping groups of sequential variants across the genome. MethodsWe conducted a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer (CRC) data from the Colon Cancer Family Registry (CCFR) (5,735 cases and 3,688 controls), and GECCO (8,865 cases and 10,285 controls) studies. A DEPTH score >1 was used to identify risk regions common to both studies. We compared DEPTH results against those from conventional GWAS analyses of these two studies as well as against 132 published risk regions. ResultsInitial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) risk regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 likely risk regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 likely risk regions that would not be detected using conventional GWAS methods, nor had they been identified in previous CRC GWASs. We found four reproducible risk regions (2q22.2, 2q33.1, 6p21.32, 13q14.3), with the HLA locus at 6p21 having the highest DEPTH score. The strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data. ConclusionDEPTH can identify novel likely risk regions for CRC not identified using conventional analyses of much larger datasets. ImpactDEPTH has potential as a powerful complementary tool to conventional GWAS analyses for identifying risk regions within the genome.

BackgroundDeleterious germline variants in ATM and CHEK2 have been associated with a moderately increased risk of breast cancer. Risks for other cancers remain unclear, and require further investigation. MethodsCancer associations for coding variants in ATM and CHEK2 were evaluated using whole-exome sequenced data from UK Biobank linked to cancer registration data (348,488 participants), and analysed both as a retrospective case-control and a prospective cohort study. Odds ratios, hazard ratios, and combined relative risks (RRs) were estimated by cancer type and gene. Separate analyses were performed for protein-truncating variants (PTVs) and rare missense variants (rMSVs; allele frequency <0{middle dot}1%). ResultsPTVs in ATM were associated with increased risks of nine cancers at p<0{middle dot}001 (pancreas, oesophagus, lung, melanoma, breast, ovary, prostate, bladder, lymphoid leukaemia [LL]), and two at p<0{middle dot}05 (colon, diffuse non-Hodgkins lymphoma [DNHL]). Carriers of rMSVs had increased risks of four cancers (p<0{middle dot}05: stomach, pancreas, prostate, Hodgkins disease [HD]). RRs were highest for breast, prostate, and any cancer where rMSVs lay in the FAT or PIK domains, and had a CADD score in the highest quintile. PTVs in CHEK2 were associated with three cancers at p<0{middle dot}001 (breast, prostate, HD), and six at p<0{middle dot}05 (oesophagus, melanoma, ovary, kidney, DNHL, myeloid leukaemia). Carriers of rMSVs had increased risks of five cancers (p<0{middle dot}001: breast, prostate, LL; p<0{middle dot}05: melanoma, multiple myeloma). ConclusionPTVs in ATM and CHEK2 are associated with a wide range of cancers, with the highest RR for pancreatic cancer in ATM PTV carriers. These findings can inform genetic counselling of carriers. WHAT IS ALREADY KNOWN ON THIS TOPICO_LIWhile previous research shows there is evidence for association between variants in ATM or CHEK2 and multiple cancer types in individual smaller studies, the associations have not been consistently evaluated across all cancer types and, with the exception of breast cancer, the strengths of association are unclear. C_LI WHAT THIS STUDY ADDSO_LIWe examined data from a large cohort study to derive relative and absolute risks for all cancer types for carriers of PTVs and rMSVs in CHEK2 and ATM . C_LIO_LIATM PTVs were associated with significantly increased risk for 11 of 23 sites examined (nine at p<0{middle dot}001), with the relative risk being highest for pancreatic cancer (approximately seven-fold). Carriers of rMSVs had increased risks of four cancers, with a RR of approximately 1{middle dot}5. C_LIO_LIFor CHEK2 PTVs, statistically significant risks were observed for seven of the 21 sites examined (one at p<0{middle dot}001). Carriers of rMSVs had increased risks of five cancers with the risk being highest for lymphoid leukaemia (approximately two-fold). C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIATM and CHEK2 are included on many cancer gene panels used in family cancer clinics, and the risk estimates from these analyses can inform genetic counselling for carriers. C_LIO_LIThe estimated absolute risks for pancreatic cancer in ATM PTV carriers (11% in males and 8% in females by age 85) are notably higher than for other major pancreatic susceptibility genes including BRCA2, CDK2NA, and PALB2. Our findings can also inform NICE guidelines for pancreatic cancer, which do not currently include ATM . C_LI

Relatives of bladder cancer (BCa) patients have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking related behaviors that may concentrate in some families. We demonstrate a new method to simultaneously assess risks for multiple cancers to identify distinct multi-cancer configurations (multiple different cancer types that cluster in relatives) surrounding BCa patients. We identified 6,416 individuals with urothelial carcinoma and familial information using the Utah Cancer Registry and Utah Population Database (UPDB). First-degree relatives, second-degree relatives, and first cousins were used to construct a familial enrichment matrix for cancer-types previously shown to be individually associated with BCa. K-medioids clustering were used to identify Familial Multi-Cancer Configurations (FMC). A case-control design and Cox regression with a 1:5 ratio of BCa cases to cancer-free controls was used to quantify the risk in specific relative-types and spouses in each FMC. Clustering analysis revealed 12 distinct FMCs, each exhibiting a different pattern of cancer co-aggregation. Of the 12 FMCs, four exhibited strong familial risk of bladder cancer along with specific patterns of increased risk of cancers in other sites (BCa FMCs), and were the focus of further investigation. Cancers at increased risk in these four BCa FMCs most commonly included melanoma, prostate and breast cancer and less commonly included leukemia, lung, pancreas and kidney cancer. A network-based approach can be used with familial data to discover new phenotype clusters for BCa, providing new directions for discovering patterns of cancer clustering.

Genome-wide association studies (GWAS) of oral cancers (OC) to date have focused predominantly on European Ancestry (EA) populations. India faces an excess burden of OC, but the most common site of occurrence is the cancer of the buccal mucosa, which is relatively rare in EA populations. We conducted a GWAS of buccal mucosa cancer (BMC) comprising 2,160 BMC cases and 2,325 controls from different geographical locations in India. Single-SNP association tests detected one novel locus (6q27) and one novel signal within the known OC risk locus 5p13.33, at the genome-wide significance level (P-value<5X10-8). We additionally conducted a GWAS of 397 BMC cases and 439 controls from Taiwan and performed multi-ancestry GWAS meta-analysis of OC on 5255 cases and 8748 controls across EA, Indian and Taiwanese populations. We identified a novel risk locus harbouring the tumour suppressor gene NOTCH1 through a gene-level analysis of the multi-ancestry GWAS data. Pathway analysis suggested that PD-1 signalling, and Interferon Gamma Signalling may be important in the aetiology of BMC. Within data from the Indian BMC GWAS, we further identified statistically significant evidence of both multiplicative interactions (P-value=0.026) indicating stronger polygenic risk of BMC among individuals with history of chewing tobacco compared to those without. Our study provides insights into the etiologies of BMC in India, highlighting both its similarities and differences with other types of oral cavity cancers, as well as the interactions between polygenic gene score and tobacco chewing.

BackgroundColorectal cancer (CRC) is a complex disease with monogenic, polygenic and environmental risk factors. Polygenic risk scores (PRS) are being developed to identify high polygenic risk individuals. Due to differences in genetic background, PRS distributions vary by ancestry, necessitating calibration. MethodsWe compared four calibration methods using the All of Us Research Program Whole Genome Sequence data for a CRC PRS previously developed in participants of European and East Asian ancestry. The methods contrasted results from linear models with A) the entire data set or an ancestrally diverse training set AND B) covariates including principal components of ancestry or admixture. Calibration with the training set adjusted the variance in addition to the mean. ResultsAll methods performed similarly within ancestry with OR (95% C.I.) per s.d. change in PRS: African 1.5 (1.02, 2.08), Admixed American 2.2 (1.27, 3.85), European 1.6 (1.43, 1.89), and Middle Eastern 1.1 (0.71, 1.63). Using admixture and an ancestrally diverse training set provided distributions closest to standard Normal with accurate upper tail frequencies. ConclusionAlthough the PRS is predictive of CRC risk for most ancestries, its performance varies by ancestry. Post-hoc calibration preserves the risk prediction within ancestries. Training a calibration model on ancestrally diverse participants to adjust both the mean and variance of the PRS, using admixture as covariates, created standard Normal z-scores. These z-scores can be used to identify patients at high polygenic risk, and can be incorporated into comprehensive risk scores including other known risk factors, allowing for more precise risk estimates.

ObjectiveOsteoradionecrosis of the jaw (ORNJ) is a chronic radiation-associated toxicity that lacks standardized classification criteria and treatment guidelines. Understanding early signs of tissue injury could help us better predict, prevent, and conservatively manage ORN. Our primary aims were to identify initial clinically-detected signs of ORN, determine the frequency of imaging-detected ORNJ, and validate the ability to classify cases using the novel system, ClinRad. Study DesignA retrospective electronic health record review of 91 patients treated for head and neck cancer at The University of Texas MD Anderson Cancer Center with suspected ORN was performed by an Oral Medicine specialist to identify initial signs of ORN. Patients who received reirradiation to the head and neck or did not have enough evidence of ORN were excluded. A descriptive analysis was performed. Results51 patients met the inclusion criteria. Half (53%) presented with imaging findings and exposed bone. Imaging findings in the absence of bone exposure were identified in 37%, of which disease progression was observed in 26%. All cases were classifiable using ClinRad. ConclusionSubclinical signs of bony changes consistent with ORN may be evident on imaging without exposed bone, supporting the use of imaging surveillance. ClinRad provided a mechanism to classify all cases at early onset. Data availability statementAnonymized data for the reported analyses is made publicly available on figshare at 10.6084/m9.figshare.28292186. Reporting guideline compliance statementIn accordance with the EQUATOR Network (Enhancing the QUAlity and Transparency Of health Research) guidance, we have utilized the RECORD checklist, a guideline for the "REporting of studies Conducted using Observational Routinely-collected health data" (Benchimool El at al., 2015) The RECORD checklist is provided as a Supplementary file and available via 10.6084/m9.figshare.28292219. Data was anonymized in accordance with the EQUATOR guideline "Preparing raw clinical data for publication: guidance for journal editors, authors, and peer reviewers" (Hrynaszkiewicz I et al., 2010).

Purpose/Objective(s)Osteoradionecrosis of the jaw (ORN) is a severe complication of head and neck cancer (HNC) radiotherapy (RT), significantly impacting patient quality of life. Current dose assessment relies on whole-mandible dosimetry, limiting personalized, tooth-specific region risk evaluation. The lack of standardized methods to document and analyze dose distributions to tooth-bearing regions further hampers dental and maxillofacial decision-making. This study develops and evaluates RADMAP, a (semi-)automated tool for segmenting tooth-based jaw regions, enabling patient- and tooth-specific radiation dose mapping to improve dental dose reporting and ORN risk assessment. Methods and MaterialsA total of 736 tooth locations from 23 HNC patients treated with definitive RT were analyzed, including 11 who developed ORN. The RADMAP tool applies an angular ray-based algorithm to automatically segment the mandible and maxilla into 32 tooth-specific jaw regions, with optional manual refinement (semi-automated), outputting radiation dose mapping in both tabular and odontogram formats. Mean dose values from manually contoured tooth roots were compared with RADMAP-segmented alveolar regions (fully and semi-automated). Interobserver agreement among six users was evaluated. Whole-mandible, manual tooth, and tooth-based jaw segment (alveolar and basal) doses were compared between regions with and without ORN development. ResultsMean dose correlation between RADMAP-segmented alveolar jaw regions and manually segmented tooth roots was high for both fully and semi-automated approaches (R{superscript 2} = 0.98, p<0.0001), demonstrating accurate dose estimation. Interobserver agreement showed 95% limits of {+/-}2.9 Gy for mandibular alveolar segments, confirming reproducibility. Tooth-based jaw segments showed a significant differentiation in radiation dose for the ORN-positive versus ORN-negative sites (difference in mean dose (DIM): 12.4 {+/-}3.7 Gy, p=0.0008), which was not seen when considering the whole-mandible dose (DIM=6.2 {+/-}4.3 Gy, p=0.17), demonstrating RADMAPs promise for improved ORN risk assessment. ConclusionRADMAP enables accurate, tooth-specific dose mapping of the mandible and maxilla, and potential improved ORN risk differentiation beyond whole-mandible dosimetry. Tooth-based dose reporting can personalize treatment, enhance multidisciplinary communication, and support prevention of radiation-related orodental sequelae.

PurposeOsteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. MethodsConsecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT ([&ge;]45Gy) in 2011-2018 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared to fifteen existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection). ResultsORN was identified in 219 out of 2732 (8%) consecutive HNC patients. Factors associated with high-risk of ORN were: oral-cavity or oropharyngeal primaries, received IMRT dose [&ge;]60Gy, current/ex-smokers, and/or stage III-IV periodontal disease. The ORN rate for high-risk vs low-risk patients was 12.7% vs 3.1% (p<0.001) with an area-under-the-receiver-operating-curve (AUC) of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, RadORN, was proposed based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems. ConclusionWe identified risk factors for ORN, and proposed a novel ORN classification system based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN, and may facilitate clinical care and clinical trials.

ImportanceMammographic density (MD) and pathogenic variants (PVs) in breast cancer susceptibility genes are major determinants of breast cancer risk, but their association and joint effects on breast cancer risk are unclear. ObjectiveTo investigate the association between the presence or absence of PVs in breast cancer susceptibility genes and MD measures, and their joint effects on breast cancer risk in an observational study; and to evaluate causality using Mendelian randomisation (MR) analyses. DesignCase-control analyses using data from the Breast Cancer Association Consortium (1991-2016). Sequencing and genotyping took place between 2009 and 2021. SettingMulticenter ParticipantsA total of 6,809 cases and 18,189 controls were included, from 15 studies, comprising women aged 19 to 92 years with mammograms taken at least one year before diagnosis. ExposureMD measures, including dense area (DA), non-dense area (NDA), percentage density (PD) and absolute difference in PD between left and right breasts (ADPD), and PVs in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C and RAD51D. Main outcomes and measuresBreast cancer risk overall, by oestrogen receptor expression-defined subtypes, and among BRCA1 and BRCA2 PV carriers. ResultsNo association was found between the overall burden of PVs and any MD measure. There was some evidence for a negative interaction between the burden of PVs in the eight genes and PD (OR=0.79,95%CIint=0.62,1.00, PLRT=0.047). This appears to be largely driven by a positive interaction with NDA. MR analyses indicated attenuated effects for BRCA1 (for PD, OR per standard deviation =1.02(95%CI:0.78,1.34) but not BRCA2 PV carriers (1.54,95%CI=1.08,2.24)). Conclusions and RelevanceThere was no evidence of association between PVs in breast cancer susceptibility genes and MD measures, but some suggestion that the association between MD and breast cancer risk may be weaker in PV carriers. Replication of these findings in further large datasets is required.

BackgroundSubsequent primary malignancies following human papillomavirus (HPV)-related cancers represent an important survivorship concern. However, evidence remains limited regarding sociodemographic and clinical factors associated with registry-defined subsequent cancers among children, adolescents, and young adults in U.S. population-based cohorts. MethodsWe conducted a retrospective population-based analysis of 1,326 individuals diagnosed with HPV-related cancers using Surveillance, Epidemiology, and End Results (SEER) data. Registry-defined subsequent cancer was operationalized as the occurrence of additional primary HPV-related malignancies according to SEER multiple primary rules. Multivariable logistic regression models estimated associations with sex, age group, area-level socioeconomic status (Yost Index quintiles), persistent poverty census tract status, and primary cancer site. Sex-stratified analyses by cancer site were performed. ResultsRegistry-defined subsequent cancers were significantly associated with female sex and young adult age (20-29 years). Females had higher odds of subsequent cancer compared with males (OR = 1.06, 95% CI: 1.03-1.10), and individuals aged 20-29 years had higher odds than those aged 0-9 years (OR = 1.10, 95% CI: 1.05-1.16). Associations persisted after adjustment for socioeconomic indicators. No significant associations were observed with Yost Index quintiles or persistent poverty. Sex-stratified analyses showed higher odds of subsequent cancer for anal cancer among males and vulvar cancer among females relative to oropharyngeal cancer. ConclusionsSex and age are key determinants of registry-defined subsequent cancers following HPV-related malignancies, independent of area-level socioeconomic context. These findings support age- and sex-specific survivorship surveillance strategies across early life-course stages.