Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.

BACKGROUND: Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen. METHODS: Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set. RESULTS: The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95). CONCLUSIONS: We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.

Diagnostic accuracy of HPV16 early antigen serology for HPV-driven oropharyngeal cancer is independent of age and sex.

A growing proportion of head and neck cancer (HNC), especially oropharyngeal cancer (OPC), is caused by human papillomavirus (HPV). There are several markers for HPV-driven HNC, one being HPV early antigen serology. We aimed to investigate the diagnostic accuracy of HPV serology and its performance across patient characteristics. Data from the VOYAGER consortium was used, which comprises five studies on HNC from North America and Europe. Diagnostic accuracy, that is, sensitivity, specificity, Cohen's kappa and correctly classified proportions of HPV16 E6 serology, was assessed for OPC and other HNC using p16INK4a immunohistochemistry (p16), HPV in situ hybridization (ISH) and HPV PCR as reference methods. Stratified analyses were performed for variables including age, sex, smoking and alcohol use, to test the robustness of diagnostic accuracy. A risk-factor analysis based on serology was conducted, comparing HPV-driven to non-HPV-driven OPC. Overall, HPV serology had a sensitivity of 86.8% (95% CI 85.1-88.3) and specificity of 91.2% (95% CI 88.6-93.4) for HPV-driven OPC using p16 as a reference method. In stratified analyses, diagnostic accuracy remained consistent across sex and different age groups. Sensitivity was lower for heavy smokers (77.7%), OPC without lymph node involvement (74.4%) and the ARCAGE study (66.7%), while specificity decreased for cases with <10 pack-years (72.1%). The risk-factor model included study, year of diagnosis, age, sex, BMI, alcohol use, pack-years, TNM-T and TNM-N stage. HPV serology is a robust biomarker for HPV-driven OPC, and its diagnostic accuracy is independent of age and sex. Future research is suggested on the influence of smoking on HPV antibody levels.

Blast-Derived Small Extracellular Vesicles in the Plasma of Patients with Acute Myeloid Leukemia Predict Responses to Chemotherapy.

The small extracellular vesicles (sEV) accumulating in acute myeloid leukemia (AML) patients' plasma are mixtures of vesicles produced by leukemic and non-malignant cells. sEV originating from leukemia blasts could serve as potential non-invasive biomarkers of AML response to therapy. To isolate blast-derived sEV from patients' plasma, we developed a bioprinted microarray-based immunoassay using monoclonal antibodies (mAbs) specific for leukemia-associated antigens (LAAs) and mAbs specific for a mix of tetraspanins (CD9, CD63, and CD81). We determined the proportion of LAA+ sEV relative to total plasma sEV (the LAA+/total sEV ratio) in serially collected samples of newly diagnosed AML patients prior to, during, and after chemotherapy. At AML diagnosis, the LAA+/total sEV ratio was significantly higher in patients than in healthy donors (HDs). In patients who achieved complete remission (CR) after induction chemotherapy, the LAA+/total sEV ratios significantly decreased after each chemotherapy cycle to levels seen in HDs. In contrast, the LAA+/total sEV ratios in AML patients with persistent leukemia after therapy remained elevated during and after therapy, as did the percentage of leukemic blasts in these patients' bone marrows. The LAA+/total sEV ratio emerges as a promising non-invasive biomarker of leukemia response to therapy.

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples.

Multiplexed imaging technologies have made it possible to interrogate complex tumor microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily and accurately segment cells into their sub-cellular compartments. Within the supervised learning paradigm, deep learning based segmentation methods demonstrating human level performance have emerged. Here we present an unsupervised segmentation (UNSEG) method that achieves deep learning level performance without requiring any training data. UNSEG leverages a Bayesian-like framework and the specificity of nucleus and cell membrane markers to construct an a posteriori probability estimate of each pixel belonging to the nucleus, cell membrane, or background. It uses this estimate to segment each cell into its nuclear and cell-membrane compartments. We show that UNSEG is more internally consistent and better at generalizing to the complexity of tissue samples than current deep learning methods. This allows UNSEG to unambiguously identify the cytoplasmic compartment of a cell, which we employ to demonstrate its use in an example biological scenario. Within the UNSEG framework, we also introduce a new perturbed watershed algorithm capable of stably and accurately segmenting a cell nuclei cluster into individual cell nuclei. Perturbed watershed can also be used as a standalone algorithm that researchers can incorporate within their supervised or unsupervised learning approaches to replace classical watershed. Finally, as part of developing UNSEG, we have generated a high-quality annotated gastrointestinal tissue dataset, which we anticipate will be useful for the broader research community. Segmentation, despite its long antecedents, remains a challenging problem, particularly in the context of tissue samples. UNSEG, an easy-to-use algorithm, provides an unsupervised approach to overcome this bottleneck, and as we discuss, can help improve deep learning based segmentation methods by providing a bridge between unsupervised and supervised learning paradigms.

Male sex and pretreatment weight loss are associated with poor outcome in patients with advanced non-small cell lung cancer treated with immunotherapy: a retrospective study.

The influence of sex and body mass index (BMI) on the efficacy of immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (NSCLC) patients remains unclear. We conducted a retrospective study to evaluate the relationship between sex, BMI, pretreatment weight loss (PWL), and clinical outcomes in 399 stage IV NSCLC patients treated with ICIs using data abstracted from medical records. Multivariable Cox proportional hazards models were used to assess the impact on overall survival and progression-free survival. Females were significantly more likely to experience immune-related adverse events and had a significantly lower risk of death compared to males in our patient cohort. In stratified analyses, the latter was limited to those receiving first-line monotherapy. BMI was overall not significantly associated with outcome. However, underweight patients had a significantly higher risk of both progression and death compared to normal weight patients in the first-line monotherapy group. When stratified by sex, underweight males had a significantly higher risk of progression and death compared to normal weight males. This was not observed among females. Those with PWL had overall significantly worse outcomes compared to those without. In stratified analyses, PWL was associated with significantly worse OS in both females and males. Stratified by treatment, the worse outcome was limited to those receiving ICI monotherapy. In summary, utilizing real-world data, this study suggests that male sex, being underweight, and PWL negatively impact ICI efficacy in NSCLC patients. Therapeutic approaches to improve ICI outcomes in underweight patients and those with PWL should be investigated.

Impact of the COVID-19 pandemic on cancer patients in western Pennsylvania: rural-urban disparities.

PURPOSE: Disparities in cancer care persist between patients living in rural versus urban areas. The COVID-19 pandemic may have impacted concerns related to care and personal health differently in rural cancer patients. Using survey data collected from cancer patients in western Pennsylvania, we examined pandemic-related distress, concerns related to cancer care, impact on personal health, and the extent to which these differed by urban-rural residence. METHODS: Patients filled out an initial survey in August-December 2020; a second survey was completed in March 2021. The following patient concerns related to the pandemic were evaluated: threat of COVID-19 to their health, pandemic-related distress, perceptions of cancer care, and vaccine hesitancy. Multivariable logistic regression models were used to examine relationships between these outcomes and urban-rural residence as well as patient-related factors, including anxiety symptoms and social support. RESULTS: The study sample included 1,980 patients, 17% resided in rural areas. COVID-19 represented a major or catastrophic threat to personal health for 39.7% of rural and 49.0% of urban patients (p = 0.0017). Patients with high general anxiety were 10-times more likely to experience pandemic-related distress (p < 0.001). In the follow-up survey (n = 983), vaccine hesitancy was twice as prevalent among rural patients compared to urban (p = 0.012). CONCLUSIONS: The extent to which perceptions of the threat of COVD-19 to personal health and vaccine hesitancy exacerbates rural-urban disparities in cancer care and prognosis warrants further study. Cancer patients may be vulnerable to heightened anxiety and distress triggered by the pandemic.

Soluble CD137 and risk of hepatocellular carcinoma: nested case-control studies in cohorts in Shanghai and Singapore.

BACKGROUND: The majority of hepatocellular carcinoma (HCC) cases occur in the presence of cirrhosis. Biomarkers of cirrhosis-associated immune dysfunction such as CD8+ T cell cytokines could aid HCC risk assessment. METHODS: CD8+ T cell cytokines were determined in pre-diagnostic serum in two studies including 315 HCC case-control pairs in the Shanghai Cohort Study (SCS) and 197 pairs in the Singapore Chinese Health Study (SCHS). Conditional logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (CI) for HCC with levels of five cytokines-soluble CD137 (sCD137), soluble Fas (sFas), perforin, macrophage inflammatory protein 1-beta (MIP-1ß), and tumour necrosis factor alpha (TNF-α). RESULTS: sCD137 levels were significantly higher in HCC cases than controls in both cohorts (Ps < 0.001). Compared with the lowest quartile, multivariable-adjusted ORs (95% CI) of HCC for the highest sCD137 quartile were 3.79 (1.73, 8.30) in the SCS and 3.49 (1.44, 8.48) in the SCHS. The sCD137-HCC association was independent of hepatitis B seropositivity and follow-up time. No other cytokine was consistently associated with HCC risk. CONCLUSION: sCD137 was associated with higher risk of HCC in two studies nested in general population cohorts. sCD137 may be a long-term risk marker of HCC development.

Randomized, Double-Blind, Placebo-Controlled Trial of MUC1 Peptide Vaccine for Prevention of Recurrent Colorectal Adenoma.

PURPOSE: To assess whether MUC1 peptide vaccine produces an immune response and prevents subsequent colon adenoma formation. PATIENTS AND METHODS: Multicenter, double-blind, placebo-controlled randomized trial in individuals age 40 to 70 with diagnosis of an advanced adenoma ≤1 year from randomization. Vaccine was administered at 0, 2, and 10 weeks with a booster injection at week 53. Adenoma recurrence was assessed ≥1 year from randomization. The primary endpoint was vaccine immunogenicity at 12 weeks defined by anti-MUC1 ratio ≥2.0. RESULTS: Fifty-three participants received the MUC1 vaccine and 50 placebo. Thirteen of 52 (25%) MUC1 vaccine recipients had a ≥2-fold increase in MUC1 IgG (range, 2.9-17.3) at week 12 versus 0/50 placebo recipients (one-sided Fisher exact P < 0.0001). Of 13 responders at week 12, 11 (84.6%) responded to a booster injection at week 52 with a ≥2-fold increase in MUC1 IgG measured at week 55. Recurrent adenoma was observed in 31 of 47 (66.0%) in the placebo group versus 27 of 48 (56.3%) in the MUC1 group [adjusted relative risk (aRR), 0.83; 95% confidence interval (CI), 0.60-1.14; P = 0.25]. Adenoma recurrence occurred in 3/11 (27.3%) immune responders at week 12 and week 55 (aRR, 0.41; 95% CI, 0.15-1.11; P = 0.08 compared with placebo). There was no difference in serious adverse events. CONCLUSIONS: An immune response was observed only in vaccine recipients. Adenoma recurrence was not different than placebo, but a 38% absolute reduction in adenoma recurrence compared with placebo was observed in participants who had an immune response at week 12 and with the booster injection.

Prognostic role of detailed colorectal location and tumor molecular features: analyses of 13,101 colorectal cancer patients including 2994 early-onset cases.

BACKGROUND: The pathogenic effect of colorectal tumor molecular features may be influenced by several factors, including those related to microbiota, inflammation, metabolism, and epigenetics, which may change along colorectal segments. We hypothesized that the prognostic association of colon cancer location might differ by tumor molecular characteristics. METHODS: Utilizing a consortium dataset of 13,101 colorectal cancer cases, including 2994 early-onset cases, we conducted survival analyses of detailed tumor location stratified by statuses of microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF oncogenic mutation. RESULTS: There was a statistically significant trend for better colon cancer-specific survival in relation to tumor location from the cecum to sigmoid colon (Ptrend = 0.002), excluding the rectum. The prognostic association of colon location differed by MSI status (Pinteraction = 0.001). Non-MSI-high tumors exhibited the cecum-to-sigmoid trend for better colon cancer-specific survival [Ptrend < 0.001; multivariable hazard ratio (HR) for the sigmoid colon (vs. cecum), 0.80; 95% confidence interval (CI) 0.70-0.92], whereas MSI-high tumors demonstrated a suggestive cecum-to-sigmoid trend for worse survival (Ptrend = 0.020; the corresponding HR, 2.13; 95% CI 1.15-3.92). The prognostic association of colon tumor location also differed by CIMP status (Pinteraction = 0.003) but not significantly by age, stage, or other features. Furthermore, MSI-high status was a favorable prognostic indicator in all stages. CONCLUSIONS: Both detailed colonic location and tumor molecular features need to be accounted for colon cancer prognostication to advance precision medicine. Our study indicates the important role of large-scale studies to robustly examine detailed colonic subsites in molecular oncology research.

A risk prediction model for head and neck cancers incorporating lifestyle factors, HPV serology and genetic markers.

Head and neck cancer is often diagnosed late and prognosis for most head and neck cancer patients remains poor. To aid early detection, we developed a risk prediction model based on demographic and lifestyle risk factors, human papillomavirus (HPV) serological markers and genetic markers. A total of 10 126 head and neck cancer cases and 5254 controls from five North American and European studies were included. HPV serostatus was determined by antibodies for HPV16 early oncoproteins (E6, E7) and regulatory early proteins (E1, E2, E4). The data were split into a training set (70%) for model development and a hold-out testing set (30%) for model performance evaluation, including discriminative ability and calibration. The risk models including demographic, lifestyle risk factors and polygenic risk score showed a reasonable predictive accuracy for head and neck cancer overall. A risk model that also included HPV serology showed substantially improved predictive accuracy for oropharyngeal cancer (AUC = 0.94, 95% CI = 0.92-0.95 in men and AUC = 0.92, 95% CI = 0.88-0.95 in women). The 5-year absolute risk estimates showed distinct trajectories by risk factor profiles. Based on the UK Biobank cohort, the risks of developing oropharyngeal cancer among 60 years old and HPV16 seropositive in the next 5 years ranged from 5.8% to 14.9% with an average of 8.1% for men, 1.3% to 4.4% with an average of 2.2% for women. Absolute risk was generally higher among individuals with heavy smoking, heavy drinking, HPV seropositivity and those with higher polygenic risk score. These risk models may be helpful for identifying people at high risk of developing head and neck cancer.

Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program.

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.

Early natural menopause is associated with poor lung health and increased mortality among female smokers.

BACKGROUND: Early natural menopause has been regarded as a biomarker of reproductive and somatic aging. Cigarette smoking is the most harmful factor for lung health and also an established risk factor for early menopause. Understanding the effect of early menopause on health outcomes in middle-aged and older female smokers is important to develop preventive strategies. OBJECTIVE: This study aimed to examine the associations of early menopause with multiple lung health and aging biomarkers, lung cancer risk, and all-cause and cause-specific mortality in postmenopausal women who were moderate or heavy smokers. STUDY DESIGN: This study was conducted on postmenopausal women with natural (n=1038) or surgical (n=628) menopause from the Pittsburgh Lung Screening Study. The Pittsburgh Lung Screening Study is a community-based research cohort of current and former smokers, screened with low-dose computed tomography and followed up for lung cancer. Early menopause was defined as occurring before 45 years of age. The analyses were stratified by menopause types because of the different biological and medical causes of natural and surgical menopause. Statistical methods included linear model, generalized linear model, linear mixed-effects model, and time-to-event analysis. RESULTS: The average age of the 1666 female smokers was 59.4±6.7 years, with 1519 (91.2%) of the population as non-Hispanic Whites and 1064 (63.9%) of the population as current smokers at baseline. Overall, 646 (39%) women reported early menopause, including 198 (19.1%) women with natural menopause and 448 (71.3%) women with surgical menopause (P<.001). Demographic variables did not differ between early and nonearly menopause groups, regardless of menopause type. Significant associations were identified between early natural menopause and higher risk of wheezing (odds ratio, 1.65; P<.01), chronic bronchitis (odds ratio, 1.73; P<.01), and radiographic emphysema (odds ratio, 1.70; P<.001) and lower baseline lung spirometry in an obstructive pattern (-104.8 mL/s for forced expiratory volume in the first second with P<.01, -78.6 mL for forced vital capacity with P=.04, and -2.1% for forced expiratory volume in the first second-to-forced vital capacity ratio with P=.01). In addition, early natural menopause was associated with a more rapid decline of forced expiratory volume in the first second-to-forced vital capacity ratio (-0.16% per year; P=.01) and incident airway obstruction (odds ratio, 2.02; P=.04). Furthermore, women early natural menopause had a 40% increased risk of death (P=.023), which was mainly driven by respiratory diseases (hazard ratio, 2.32; P<.001). Mediation analyses further identified that more than 33.3% of the magnitude of the associations between early natural menopause and all-cause and respiratory mortality were explained by baseline forced expiratory volume in the first second. Additional analyses in women with natural menopause identified that the associations between continuous smoking and subsequent lung cancer risk and cancer mortality were moderated by early menopause status, and females with early natural menopause who continued smoking had the worst outcomes (hazard ratio, >4.6; P<.001). This study did not find associations reported above in female smokers with surgical menopause. CONCLUSION: Early natural menopause was found to be a risk factor for malignant and nonmalignant lung diseases and mortality in middle-aged and older female smokers. These findings have strong public health relevance as preventive strategies, including smoking cessation and chest computed tomography screening, should target this population (ie, female smokers with early natural menopause) to improve their postmenopausal health and well-being.

NAFLD polygenic risk score and risk of hepatocellular carcinoma in an East Asian population.

It is difficult to identify people with nonalcoholic fatty liver disease (NAFLD) who are at high risk for developing hepatocellular carcinoma (HCC). A polygenic risk score (PRS) for hepatic fat (HFC-PRS) derived from non-Asians has been reported to be associated with HCC risk in European populations. However, population-level data of this risk in Asian populations are lacking. Utilizing resources from 24,333 participants of the Singapore Chinese Health Study (SCHS), we examined the relationship between the HFC-PRS and HCC risk. In addition, we constructed and evaluated a NAFLD-related PRS (NAFLD-PRS) with HCC risk in the SCHS. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of HCC incidence with both HFC-PRS and NAFLD-PRS. The HFC-PRS and NAFLD-PRS were highly correlated (Spearman r = 0.79, p < 0.001). The highest quartiles of both the HFC-PRS and the NAFLD-PRS were associated with significantly increased risk of HCC with HR of 2.39 (95% CI 1.51, 3.78) and 1.77 (95% CI 1.15, 2.73), respectively, compared with their respective lowest quartile. Conclusion: The PRS for hepatic fat content or NAFLD may be useful for assessing HCC risk in both Asian and European populations. The findings of this and prior studies support a potential causal role of genetically determined NAFLD in HCC development.

A phase 1 and pharmacodynamic study of chronically-dosed, single-agent veliparib (ABT-888) in patients with BRCA1- or BRCA2-mutated cancer or platinum-refractory ovarian or triple-negative breast cancer.

PURPOSE: BRCA1 or BRCA2 mutated cancers (BRCAmut) have intrinsic sensitivity to PARP inhibitors due to deficiency in homologous recombination-mediated DNA repair. There are similarities between BRCAmut and BRCAwt ovarian and basal-like breast cancers. This phase I study determined the recommended phase II dose (RP2D) and preliminary efficacy of the PARP inhibitor, veliparib (ABT-888), in these patients. PATIENTS AND METHODS: Patients (n = 98) were dosed with veliparib 50-500 mg twice daily (BID). The BRCAmut cohort (n = 70) contained predominantly ovarian (53%) and breast (23%) cancers; the BRCAwt cohort (n = 28) consisted primarily of breast cancer (86%). The MTD, DLT, adverse events, PK, PD, and clinical response were assessed. RESULTS: DLTs were grade 3 nausea/vomiting at 400 mg BID in a BRCAmut carrier, grade 2 seizure at 400 mg BID in a patient with BRCAwt cancer, and grade 2 seizure at 500 mg BID in a BRCAmut carrier. Common toxicities included nausea (65%), fatigue (45%), and lymphopenia (38%). Grade 3/4 toxicities were rare (highest lymphopenia at 15%). Overall response rate (ORR) was 23% (95% CI 13-35%) in BRCAmut overall, and 37% (95% CI 21-55%) at 400 mg BID and above. In BRCAwt, ORR was 8% (95% CI 1-26%), and clinical benefit rate was 16% (95% CI 4-36%), reflecting prolonged stable disease in some patients. PK was linear with dose and was correlated with response and nausea. CONCLUSIONS: Continuous veliparib is safe and tolerable. The RP2D was 400 mg BID. There is evidence of clinical activity of veliparib in patients with BRCAmut and BRCAwt cancers.

Investigating the effect of sexual behaviour on oropharyngeal cancer risk: a methodological assessment of Mendelian randomization.

BACKGROUND: Human papilloma virus infection is known to influence oropharyngeal cancer (OPC) risk, likely via sexual transmission. However, sexual behaviour has been correlated with other risk factors including smoking and alcohol, meaning independent effects are difficult to establish. We aimed to evaluate the causal effect of sexual behaviour on the risk of OPC using Mendelian randomization (MR). METHODS: Genetic variants robustly associated with age at first sex (AFS) and the number of sexual partners (NSP) were used to perform both univariable and multivariable MR analyses with summary data on 2641 OPC cases and 6585 controls, obtained from the largest available genome-wide association studies (GWAS). Given the potential for genetic pleiotropy, we performed a number of sensitivity analyses: (i) MR methods to account for horizontal pleiotropy, (ii) MR of sexual behaviours on positive (cervical cancer and seropositivity for Chlamydia trachomatis) and negative control outcomes (lung and oral cancer), (iii) Causal Analysis Using Summary Effect estimates (CAUSE), to account for correlated and uncorrelated horizontal pleiotropic effects, (iv) multivariable MR analysis to account for the effects of smoking, alcohol, risk tolerance and educational attainment. RESULTS: In univariable MR, we found evidence supportive of an effect of both later AFS (IVW OR = 0.4, 95%CI (0.3, 0.7), per standard deviation (SD), p = < 0.001) and increasing NSP (IVW OR = 2.2, 95%CI (1.3, 3.8) per SD, p = < 0.001) on OPC risk. These effects were largely robust to sensitivity analyses accounting for horizontal pleiotropy. However, negative control analysis suggested potential violation of the core MR assumptions and subsequent CAUSE analysis implicated pleiotropy of the genetic instruments used to proxy sexual behaviours. Finally, there was some attenuation of the univariable MR results in the multivariable models (AFS IVW OR = 0.7, 95%CI (0.4, 1.2), p = 0.21; NSP IVW OR = 0.9, 95%CI (0.5 1.7), p = 0.76). CONCLUSIONS: Despite using genetic variants strongly related sexual behaviour traits in large-scale GWAS, we found evidence for correlated pleiotropy. This emphasizes a need for multivariable approaches and the triangulation of evidence when performing MR of complex behavioural traits.

Genetic variants associated with circulating C-reactive protein levels and colorectal cancer survival: Sex-specific and lifestyle factors specific associations.

Elevated blood levels of C-reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC-specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI-EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC-specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow-up, 3547 (64.8%) were due to CRC. No variants were associated with CRC-specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC-specific mortality (corrected Pinteraction  = .0004); women had higher CRC-specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04-1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82-0.94). There was no evidence of interactions between CRP-associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP-associated variant in relation to CRC-specific mortality. Future replication of this association and functional annotation of the variant are needed.

Smoking Behavior and Prognosis After Colorectal Cancer Diagnosis: A Pooled Analysis of 11 Studies.

Background: Smoking has been associated with colorectal cancer (CRC) incidence and mortality in previous studies, but current evidence on smoking in association with survival after CRC diagnosis is limited. Methods: We pooled data from 12 345 patients with stage I-IV CRC from 11 epidemiologic studies in the International Survival Analysis in Colorectal Cancer Consortium. Cox proportional hazards regression models were used to evaluate the associations of prediagnostic smoking behavior with overall, CRC-specific, and non-CRC-specific survival. Results: Among 12 345 patients with CRC, 4379 (35.5%) died (2515 from CRC) over a median follow-up time of 7.5 years. Smoking was strongly associated with worse survival in stage I-III patients, whereas no association was observed among stage IV patients. Among stage I-III patients, clear dose-response relationships with all survival outcomes were seen for current smokers. For example, current smokers with 40 or more pack-years had statistically significantly worse overall, CRC-specific, and non-CRC-specific survival compared with never smokers (hazard ratio [HR] =1.94, 95% confidence interval [CI] =1.68 to 2.25; HR = 1.41, 95% CI = 1.12 to 1.78; and HR = 2.67, 95% CI = 2.19 to 3.26, respectively). Similar associations with all survival outcomes were observed for former smokers who had quit for less than 10 years, but only a weak association with non-CRC-specific survival was seen among former smokers who had quit for more than 10 years. Conclusions: This large consortium of CRC patient studies provides compelling evidence that smoking is strongly associated with worse survival of stage I-III CRC patients in a clear dose-response manner. The detrimental effect of smoking was primarily related to noncolorectal cancer events, but current heavy smoking also showed an association with CRC-specific survival.

Germline determinants of humoral immune response to HPV-16 protect against oropharyngeal cancer.

Although several oropharyngeal cancer (OPC) susceptibility loci have been identified, most previous studies lacked detailed information on human papillomavirus (HPV) status. We conduct a genome-wide analysis by HPV16 serology status in 4,002 oral cancer cases (OPC and oral cavity cancer (OCC)) and 5,256 controls. We detect four susceptibility loci pointing to a distinct genetic predisposition by HPV status. Our most notable finding in the HLA region, that is now confirmed to be specific of HPV(+)OPC risk, reveal two independent loci with strong protective effects, one refining the previously reported HLA class II haplotype association. Antibody levels against HPV16 viral proteins strongly implicate the protective HLA variants as major determinants of humoral response against L1 capsid protein or E6 oncoprotein suggesting a natural immune response against HPV(+)OPC promoted by HLA variants. This indicates that therapeutic vaccines that target E6 and attenuate viral response after established HPV infections might protect against HPV(+)OPC.

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules.

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.