Cancer Risk Stratification Research Articles

Enhanced Risk Stratification in Early-Stage Endometrial Cancer: Integrating POLE through Droplet Digital PCR and L1CAM.

In order to enhance risk stratification in early-stage endometrial cancer (EC), we conducted molecular classification using surrogate markers, including the POLE droplet digital polymerase chain reaction (ddPCR) and L1CAM immunohistochemistry (IHC). We analyzed archival tumor tissue from 183 early-stage EC patients. POLE pathogenic mutations of P286R, V411L, S297F, A456P, and S459F within exons 9, 13, and 14 were detected using a ddPCR, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI tests. Additionally, we conducted IHC for p53 and L1CAM. The 183 ECs were categorized into four subgroups: POLE-mutated (15.9%), MMR-deficient (29.0%), p53-abnormal (8.7%), and non-specific molecular profile (NSMP, 46.4%). We further subcategorized the NSMP subgroup into NSMP-L1CAMneg (41.5%) and NSMP-L1CAMpos (4.9%), which we refer to as the molecular L1CAM classification. The molecular L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p < 0.001, each). Integrating molecular L1CAM classification can enhance risk stratification in early-stage EC, providing valuable prognostic information to guide treatment decisions and improve patient outcomes. POLE ddPCR might be a cost-effective and easy-to-perform test as an alternative to POLE NGS.

OR32-03 mRNA Expression Based Tumor Behavior Prediction Models In Thyroid Nodules

Abstract Disclosure: A. Golding: None. G. Correa: None. E. Valenzuela Sheker: None. R. Jiang: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. Y. Liu: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. J. Huang: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. R.T. Kloos: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. G.C. Kennedy: Employee; Self; Veracyte, Inc. Stock Owner; Self; Veracyte, Inc. D. Bimston: None. The 2015 ATA thyroid cancer risk stratification system is driven primarily by the extent of vascular and extrathyroidal extension, as well as lymph node metastases. The objectives of this study were to evaluate the prevalence of invasion and lymph node metastases in a cohort enriched with thyroid malignancies and provide a risk signature with a high negative predictive value ruling out these tumor features. Histopathology reports from Afirma Genomic Sequencing Classifier (GSC) algorithm training and from thyroid cancer patients managed at an integrative endocrine surgery community care practice (total 697 and ∼50% from each) were reviewed for invasion and metastases. An integer from 0-3 was assigned based on the extent of invasion (ranging from none to extensive extra-thyroidal) or extent of lymph node metastases (ranging from none to lateral node metastases). To develop predictive signatures for invasion/metastases, over 400 literature-derived expression-based signatures were evaluated; they cover a broad spectrum of molecular processes, including cancer hallmarks such as endothelial to mesenchymal transition, tumor microenvironment, immune-oncology, metabolism, and treatment sensitivity. Further, acknowledging that multiple complex molecular processes are associated with invasion/metastases, over 200 machine-learning (ML) models were trained within the repeated and nested cross-validation (CV) framework. They utilized these literature-derived signatures as well as differentially expressed genes between high and low risk of invasion/metastases as the basic building blocks. The application of top performing signatures among Bethesda (B) V/VI nodules as well as indeterminate thyroid nodules (ITN - BIII/IV) that are GSC-suspicious, showed that 40-50% of these lesions were marked as low risk for invasion/metastases. With a starting prevalence of 10.0% of high-level invasion (scored 2 or 3), 41.3% of the cohort is ruled out for clinically relevant invasion with a negative predictive value (NPV) of 97.6%. With a starting prevalence of 11.3% of high-level metastases (scored 2 or 3), 49.8% of the cohort is ruled out for clinically relevant metastases with an NPV of 98.6%. The rule-out capability represents more than 4-fold or 7-fold reduction in high-level invasion/metastases from the baseline prevalence, respectively. Expression-based signatures that confidently rule out tumor invasion and metastasis may help personalize the surgical approach for individuals. This may reduce excess surgery and overtreatment, optimizing the initial response to therapy and decreasing the rates of surgical complications and post-operative hypothyroidism. Presentation: Sunday, June 18, 2023

Prevalence of hospitalized women at high-risk for developing lung cancer

ABSTRACT Background Lung cancer screening with low-dose computer tomography (CT) has been shown to reduce the lung cancer mortality in high-risk individuals by 20%. Despite the proven mortality benefit, the utilization of lung cancer screening among high-risk populations remains low. Objective This study explores the prevalence of high-risk population for developing lung cancer among hospitalized women and evaluates the screening behavior toward other common cancers during a hospital stay. Methods This is a cross-sectional study in which 248 cancer-free hospitalized women aged 50–75 years who reported current or prior smoking were enrolled during hospital admission at an academic center. A bedside survey was conducted to collect socio-demographic, cancer screening behavior, and medical comorbidities for the study patients. Unpaired t-test and Chi-square tests were used to compare characteristics and common cancer screening behavior by lung cancer risk stratification. Results Forty-three percent of the hospitalized women were at intermediate to high-risk for developing lung cancer risk. Intermediate to high-risk women were more likely to be older, Caucasian, retired, or with a disability, and had higher comorbidity burden as compared to the low-risk group. Women at low and intermediate to high risk were equally non-adherent with breast (35% vs 31%, p = 0.59) and colorectal (32% vs 24%, p = 0.20) cancers screening guidelines. Only 38% of women from the intermediate to the high-risk group had a CT chest within the last year. Conclusion The study’s findings suggest that almost half of the hospitalized women who report current or past smoking are at high-risk for developing lung cancer.

High Risk Prognostic Factors Predictive of Outcome Following Stereotactic Body Radiation Therapy (SBRT) for Early-Stage Lung Cancer

High risk prognostic factors for outcomes following SBRT for early-stage lung cancer per SWOG/NRG 1914 include: tumor size > 2cm; moderately/poorly/undifferentiated histology; or high metabolic activity on PET/CT defined as SUV > 6.2. The purpose of this IRB approved retrospective study is to assess outcome for stage I lung cancer and to validate SWOG risk stratification in a single community-based radiation department. A total of 132 patients with 139 tumors treated with SBRT between 2014 and 2019 were stratified by SWOG risk group (high vs. low). To assess differences by risk group in estimated overall survival (OS) at the patient level, as well as Freedom from Local Failure (FFLF), Freedom from Regional Failure (FFRF) and Freedom from Distant Failure (FFDF) at the tumor level, Kaplan-Meier methodology and Cox proportional hazards (PH) modeling for correlated data were used. Statistical significance was concluded at the 0.05 level. Median follow-up for the entire group is 56 months. 77% of patients had high risk tumors. The median patient age was 75 years with 57% female. Patients with high-risk tumors were older (p = 0.023) compared to patients with low-risk tumors. At the tumor level, high risk tumors were more likely to have biopsies performed (91% vs 57% p = 0.002) and more likely to experience regional failure (28% vs 7% p = 0.005). High risk tumors were more likely to experience local failure (8% vs 0% p = NS) and distant failure (27% vs 14% p = NS). Median survival was 49 months for the whole group (46.0 months high risk, 65.1 months low risk). Actuarial OS at 5 years is 38% (35% high risk, 51% low risk). Actuarial FFLF at 5 years is 94% (93% high risk, 100% low risk). Actuarial FFRF at 5 years is 77% (72% high risk, 93% low risk). Actuarial FFDF at 5 years is 74% (70% high risk, 88% low risk). Cox PH models revealed no statistically significant differences in FFRF by risk group (p = 0.08). Excellent local control but higher regional and distant failure was demonstrated for high-risk lung tumors as defined by SWOG/NRG 1914. Clinically important decrement in outcomes were consistently noted for high-risk tumors in this sample which did not demonstrate statistical significance due to lack of events and statistical power. However, our data supports the prognostic importance of tumor size/grade and SUV for identifying patients at high risk. Further validation with larger sample sizes would contribute to our knowledge regarding risk stratification for early-stage lung cancer treated with SBRT.

Colorectal cancer risk stratification on histological slides based on survival curves predicted by deep learning

Studies have shown that colorectal cancer prognosis can be predicted by deep learning-based analysis of histological tissue sections of the primary tumor. So far, this has been achieved using a binary prediction. Survival curves might contain more detailed information and thus enable a more fine-grained risk prediction. Therefore, we established survival curve-based CRC survival predictors and benchmarked them against standard binary survival predictors, comparing their performance extensively on the clinical high and low risk subsets of one internal and three external cohorts. Survival curve-based risk prediction achieved a very similar risk stratification to binary risk prediction for this task. Exchanging other components of the pipeline, namely input tissue and feature extractor, had largely identical effects on model performance independently of the type of risk prediction. An ensemble of all survival curve-based models exhibited a more robust performance, as did a similar ensemble based on binary risk prediction. Patients could be further stratified within clinical risk groups. However, performance still varied across cohorts, indicating limited generalization of all investigated image analysis pipelines, whereas models using clinical data performed robustly on all cohorts.

Clinical Significance of Background Parenchymal Enhancement in Breast Cancer Risk Stratification.

Background parenchymal enhancement (BPE) is an established breast cancer risk factor. However, the relationship between BPE levels and breast cancer risk stratification remains unclear. To evaluate the clinical relationship between BPE levels and breast cancer risk with covariate adjustments for age, ethnicity, and hormonal status. Retrospective. 954 screening breast MRI datasets representing 721 women divided into four cohorts: women with pathogenic germline breast cancer (BRCA) mutations (Group 1, N = 211), women with non-BRCA germline mutations (Group 2, N = 60), women without high-risk germline mutations but with a lifetime breast cancer risk of ≥20% using the Tyrer-Cuzick model (Group 3, N = 362), and women with <20% lifetime risk (Group 4, N = 88). 3 T/axial non-fat-saturated T1, short tau inversion recovery, fat-saturated pre-contrast, and post-contrast T1-weighted images. Data on age, body mass index, ethnicity, menopausal status, genetic predisposition, and hormonal therapy use were collected. BPE levels were evaluated by two breast fellowship-trained radiologists independently in accordance with BI-RADS, with a third breast fellowship-trained radiologist resolving any discordance. Propensity score matching (PSM) was utilized to adjust covariates, including age, ethnicity, menopausal status, hormonal treatments, and prior bilateral oophorectomy. The Mann-Whitney U test, chi-squared test, and univariate and multiple logistic regression analysis were performed, with an odds ratio (OR) and corresponding 95% confidence interval. Weighted Kappa statistic was used to assess inter-reader variation. A P value <0.05 indicated a significant result. In the assessment of BPE, there was substantial agreement between the two interpreting radiologists (κ = 0.74). Patient demographics were not significantly different between patient groups after PSM. The BPE of Group 1 was significantly lower than that of Group 4 and Group 3 among premenopausal women. In estimating the BPE level, the OR of gene mutations was 0.35. Adjusting for potential confounders, the BPE level of premenopausal women with BRCA mutations was significantly lower than that of non-high-risk women. 3 TECHNICAL EFFICACY: Stage 3.

System analysis based on the lysosome-related genes identifies HPS4 as a novel therapy target for liver hepatocellular carcinoma.

Liver cancer is a leading cause of cancer-related deaths worldwide. Lysosomal dysfunction is implicated in cancer progression; however, prognostic prediction models based on lysosome-related genes (LRGs) are lacking in liver cancer. This study aimed to establish an LRG-based model to improve prognosis prediction and explore potential therapeutic targets in liver cancer. Expression profiles of 61 LRGs were analyzed in The Cancer Genome Atlas liver cancer cohorts. There were 14 LRGs identified, and their association with clinical outcomes was evaluated. Unsupervised clustering, Cox regression, and functional assays were performed. Patients were classified into high-risk and low-risk subgroups based on the 14 LRGs. The high-risk group had significantly worse overall survival. Aberrant immune infiltration and checkpoint expression were observed in the high-risk group. Furthermore, HPS4 was identified as an independent prognostic indicator. Knockdown of HPS4 suppressed liver cancer cell proliferation and induced apoptosis. This study developed an LRG-based prognostic model to improve risk stratification in liver cancer. The potential value of HPS4 as a therapeutic target and biomarker was demonstrated. Regulation of HPS4 may offer novel strategies for precision treatment in liver cancer patients.

Comprehensive analysis of ICD-related lncRNAs in predicting risk stratification, clinical prognosis and immune response for breast cancer.

Breast cancer (BRCA) represents a significant threat with high mortality rates due to relapse, metastasis, and chemotherapy resistance. As a regulated cell death process characterized by the induction of immunogenic signals, immunogenic cell death (ICD) has been identified as an effective anti-tumorigenesis approach. However, the comprehensive study and its clinical value of ICD-related lncRNAs in BRCA is still missing. The transcriptome matrix and corresponding clinical information of BRCA patients were obtained from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was performed to identify ICD-related lncRNAs (ICDRLs). To determine the prognostic value of the identified ICDRLs, univariate Cox regression analysis, LASSO algorithm, and multivariate Cox regression analysis were employed to construct a risk model. The prognostic risk model was subsequently evaluated using univariate and multivariate Cox regression analysis, as well as Nomogram analysis. In vitro experiments were also conducted to validate the bioinformatics findings using quantitative real-time PCR (qRT-PCR). We established a prognostic risk signature consisting of five ICDRLs. The prognostic value of this model was subsequently confirmed in guiding BRCA prognostic stratification. Furthermore, we explored the correlation of the risk score with various clinical characteristics and chemotherapy response. qRT-PCR result confirmed the abnormal expression of ICDRLs, which was consistent with the bioinformatics data. Our findings provide evidence of the critical role of ICDRLs in BRCA and offer a novel perspective for exploring precise treatment options for BRCA patients.

Features of Ultrasound Imaging of Different Types of Thyroid Calcifications and their Association with Cancer Risk

The features of multiparametric ultrasound imaging different types of thyroid calcifications and its significance in cancer risk stratification were studied on the material of 932 patients referred for thyroid biopsy. It has been established that calcification in the thyroid gland is represented by macrocalcifications, microcalcifications, calcified capsules and fully calcified nodules with characteristic ultrasonic features. MicroPure technology was determined to improve visualization of microcalcifications, differentiate them from other hyperechogenic point structures, but was ineffective for other types of calcifications. The frequency of microcalcification in thyroid nodules is significantly associated with the risk of their malignancy, but can be detected in benign nodules and in intact parenchyma; for other types of calcifications, the dependence on the risk of malignancy is either absent or not linear. The frequency of microcalcification in thyroid nodules is significantly associated with the risk of their malignancy, but can be detected in benign nodules and in intact parenchyma; for other types of calcifications, the dependence on the risk of malignancy is either absent or not linear. Thus, ultrasound assessment of thyroid nodule calcification using MicroPure technology allows us to stratify their oncologic risk, which can be used in the choice of further patient management tactics.

Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration.

Multiomics data including imaging radiomics and various types of molecular biomarkers have been increasingly investigated for better diagnosis and therapy in the era of precision oncology. Artificial intelligence (AI) including machine learning (ML) and deep learning (DL) techniques combined with the exponential growth of multiomics data may have great potential to revolutionize cancer subtyping, risk stratification, prognostication, prediction and clinical decision-making. In this article, we first present different categories of multiomics data and their roles in diagnosis and therapy. Second, AI-based data fusion methods and modeling methods as well as different validation schemes are illustrated. Third, the applications and examples of multiomics research in oncology are demonstrated. Finally, the challenges regarding the heterogeneity data set, availability of omics data, and validation of the research are discussed. The transition of multiomics research to real clinics still requires consistent efforts in standardizing omics data collection and analysis, building computational infrastructure for data sharing and storing, developing advanced methods to improve data fusion and interpretability, and ultimately, conducting large-scale prospective clinical trials to fill the gap between study findings and clinical benefits.

Prostate Cancer–specific and All-cause Mortality After Robot-assisted Radical Prostatectomy: 20 Years’ Report from the European Association of Urology Robotic Urology Section Scientific Working Group

BackgroundEvidence on long-term oncological efficacy is available only for open radical prostatectomy but remains scarce for robot-assisted radical prostatectomy (RARP). ObjectiveTo validate the long-term survival rates after RARP and provide stratified outcomes based on contemporary prostate cancer (PCa) risk-stratification tools. Design, setting, and participantsA retrospective analysis of the European Association of Urology (EAU) Robotic Urology Section Scientific Working Group international multicenter database for RARP was performed. Patients who underwent RARP at seven pioneer robotic urology programs in Europe and the USA between 2002 and 2012 were included. Outcome measurements and statistical analysisThe primary outcomes were PCa-specific mortality and all-cause mortality. The probability of cancer-specific survival (CSS) was estimated with the competing risks method, and the probability of overall survival (OS) was estimated with the Kaplan-Meier method. Results and limitationsA total of 9876 patients who underwent RARP between 2002 and 2012 were included. Within follow-up, 1071 deaths occurred and 159 were due to PCa. At 15 yr of follow-up, CSS and OS were 97.6% (97.2%, 98.0%) and 85.5% (84.6%, 86.4%), respectively. Stratified analyses based on EAU risk groups at diagnosis and pT stage showed favorable survival rates, with low-risk (n = 4601, 46.6%), intermediate-risk (n = 4056, 41.1%), and high-risk (n = 1219, 12.3%) patients demonstrating CSS rates of 99%, 98%, and 90% at 15 yr, respectively. Notably, patients with pT3a disease had similar survival outcomes to those with pT2 disease, with worse CSS in patients with pT3b PCa (98.9% vs 97.4% vs 86.5%). Multivariable analyses identified age, prostate-specific antigen, biopsy Gleason grade group, clinical T stage, and treatment year as independent predictors of worse oncological outcomes. ConclusionsOur multicenter study with long-term follow-up confirms favorable survival outcomes after RARP for localized PCa. Patients with low- and intermediate-risk disease face a higher risk of mortality from causes other than PCa. On the contrary, high-risk patients have a significantly higher risk of PCa-specific mortality. Patient summaryIn the present study, we reported the outcomes of patients with prostate cancer (PCa) who underwent robot-assisted radical prostatectomy between 10 and 20 yr ago, and we found a very low probability of dying from PCa in patients with low- and intermediate-risk PCa.

Cardiovascular mortality by cancer risk stratification in patients with localized prostate cancer: a SEER-based study.

The risk of cardiovascular disease (CVD) mortality in patients with localized prostate cancer (PCa) by risk stratification remains unclear. The aim of this study was to determine the risk of CVD death in patients with localized PCa by risk stratification. Population-based study of 340,806 cases in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with localized PCa between 2004 and 2016. The proportion of deaths identifies the primary cause of death, the competing risk model identifies the interaction between CVD and PCa, and the standardized mortality rate (SMR) quantifies the risk of CVD death in patients with PCa. CVD-related death was the leading cause of death in patients with localized PCa, and cumulative CVD-related death also surpassed PCa almost as soon as PCa was diagnosed in the low- and intermediate-risk groups. However, in the high-risk group, CVD surpassed PCa approximately 90 months later. Patients with localized PCa have a higher risk of CVD-related death compared to the general population and the risk increases steadily with survival (SMR = 4.8, 95% CI 4.6-5.1 to SMR = 13.6, 95% CI 12.8-14.5). CVD-related death is a major competing risk in patients with localized PCa, and cumulative CVD mortality increases steadily with survival time and exceeds PCa in all three stratifications (low, intermediate, and high risk). Patients with localized PCa have a higher CVD-related death than the general population. Management of patients with localized PCa requires attention to both the primary cancer and CVD.

Detection of cervical high-grade squamous intraepithelial lesions and assessing diagnostic performance of colposcopy among women with oncogenic HPV

BackgroundHPV screening tests may improve cervical cancer risk stratification and better guide decisions about follow-up with colposcopy/biopsy. This study aimed to estimate the risk of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) among women with oncogenic HPV types and evaluate the performance of colposcopy in the diagnosis of histologic CIN2 + at Putuo Hospital, Shanghai, China.MethodsThis cross-sectional survey was conducted from February 2020 to December 2022 among women who were referred to colposcopy. Women with high-risk (HR) HPV-positive, cytology testing and colposcopy-directed biopsy were included.ResultsUnivariate and multivariate analysis indicated that high-grade colposcopic impression ((OR, 17.61%, 95%CI: 11.54–26.85%) was associated with the highest risk for detecting CIN2+, followed by HSIL + cytology (OR, 6.90%, 95%CI: 3.56–13.37%) and HPV16/18 positive (OR, 2.91%, 95%CI: 2.12–3.99%). Overall, CIN2 + was detected in 14.6% of 2007 women. HPV16/18 had higher CIN2 + risks than other HR-HPV genotypes (30.1% vs. 10.2%, P<0.001). Among women with low-grade cytology, 24.1% had CIN2+, and the risks for HPV16/18 (58.2%) were higher than for other HR-HPV(16.8%). For those with high-grade cytology, there was no significant difference between HPV groups ( 75.0% vs. 72.9%, P > 0.05). The diagnostic performance of colposcopy in diagnosis of CIN2 + by senior and junior colposcopists was comparable.ConclusionsThe results indicated that referral to colposcopy is recommended in managing women with HR-HPV positive, and colposcopic impressions provide key clues for identification CIN2+.

Cancer and idiopathic inflammatory myopathies –association of autoantibodies with carcinogenesis

The relationship between cancer development in the course of idiopathic inflammatorymyopathies (IIM) has already been noticed at the beginning of the 20th century. However, theunderlying mechanisms remain not fully understood. Risk factors for carcinogenesis in patientswith IIM include male sex, older age, and the presence of specific subtypes of inflammatorymyopathies and clinical manifestations, including dermatomyositis, dysphagia, severe skinchanges, leukocytoclastic vasculitis, acute disease onset and immunosuppressive therapyresistance. The presence of certain autoantibodies in the serum of patients with IIM is a factorof considerable importance in the stratification of cancer risk. Anti-TIF1γ autoantibodies, which might be present in even 38-80% of cancer cases in adult IIM patients, are antibodies with a wellstudiedrelationship with carcinogenesis. The relationship of other antibodies found in IIM withthe risk of carcinogenesis is still discussed. This group includes anti-NXP2, anti-HMGCR, anti-SAE1 and anti-Mi2 antibodies. Due to the contrary reports on the role of these antibodies incancer development and their relatively low prevalence in IIM, the unambiguous classificationas risk factors requires further research in larger study groups. The potential autoantibodiesutility in cancer screening in IIM patients could help detect cancer early, improving prognosisand long-term survival.

Impact of Multiparametric Magnetic Resonance Imaging for the Prediction of Extraprostatic Extension According to the National Comprehensive Cancer Network Risk Stratification in Prostate Cancer

Purpose: The accuracy of extraprostatic extension (EPE) on multiparametric magnetic resonance imaging (mpMRI) for the preoperative staging of prostate cancer (PCa) remains controversial. This study aimed to determine the effect of mpMRI for EPE prediction in the final pathology after radical prostatectomy (RP) according to the National Comprehensive Cancer Network (NCCN) risk stratification in patients with clinically localized PCa.Materials and Methods: This retrospective study analyzed 340 consecutive patients diagnosed with clinically localized PCa who underwent RP with preoperative mpMRI between March 2020 and December 2021. They were stratified according to the NCCN risk stratification into low (LR), favorable intermediate (FIR), unfavorable intermediate (UIR), and high risk (HR) groups to assess final pathological EPE. The accuracy of staging mpMRI was assessed in each group. Univariate and multivariate analyses evaluated the predictors of EPE in the final pathology after RP.Results: Preoperative mpMRI showed suspicious EPE in 87 patients (25.6%), whereas postoperative pathological evaluation revealed EPE in 137 patients (40.3%). The LR group showed relatively low sensitivity and positive predictive value compared with other groups. In the multivariate analysis, suspicious EPE on mpMRI was a significant predictive factor for EPE in the final pathology in the FIR, UIR, and HR groups (p=0.012, p=0.011, and p=0.001, respectively), whereas no correlation was observed in the LR group (p=0.711).Conclusions: A strong correlation was observed between suspicious EPE on mpMRI and EPE in the final pathology in the FIR, UIR, and HR groups but not in the LR group.

Cumulative thiopurine dosing and keratinocyte skin cancer in inflammatory bowel disease: a case-control study.

Patients with inflammatory bowel disease (IBD) treated with thiopurines are at increased risk of keratinocyte skin cancer (KSC). Most international guidelines recommend yearly dermatological screening of thiopurine-treated patients. Whether the association between the development of KSC and the use of thiopurines is dose-dependent remains unclear. The aim of this study was to investigate the association between the cumulative thiopurine dose and KSC development in patients with IBD which can be helpful to assist in further skin cancer risk stratification and personalization of screening recommendations in patients with IBD. We performed a single-center case-control study, including patients with IBD with and without a history of KSC (cases and controls, respectively). The primary outcome was the association of cumulative azathioprine, mercaptopurine and thioguanine dose with KSC development. Univariable and multivariable logistic regression analyses were performed, the latter corrected for age and smoking, known risk factors of KSC. We included 50 cases and 150 controls, predominantly white population. Age and current azathioprine use were univariably significantly associated with KSC development. In multivariable logistic regression analyses, age at inclusion remained significantly associated. Cumulative doses of thiopurines (separate or combined) or duration of thiopurine use did not impact KSC risk, also after correcting for age and smoking. Cumulative thiopurine dose and duration did not show an association with KSC development. Future KSC risk stratification, based on all available KSC risk factors, may aid in selecting individuals who can benefit most from dermatologic screening programs.

Quantifying emphysema in lung screening computed tomography with robust automated lobe segmentation.

Anatomy-based quantification of emphysema in a lung screening cohort has the potential to improve lung cancer risk stratification and risk communication. Segmenting lung lobes is an essential step in this analysis, but leading lobe segmentation algorithms have not been validated for lung screening computed tomography (CT). In this work, we develop an automated approach to lobar emphysema quantification and study its association with lung cancer incidence. We combine self-supervised training with level set regularization and finetuning with radiologist annotations on three datasets to develop a lobe segmentation algorithm that is robust for lung screening CT. Using this algorithm, we extract quantitative CT measures for a cohort () from the National Lung Screening Trial and analyze the multivariate association with lung cancer incidence. Our lobe segmentation approach achieved an external validation Dice of 0.93, significantly outperforming a leading algorithm at 0.90 (). The percentage of low attenuation volume in the right upper lobe was associated with increased lung cancer incidence (odds ratio: 1.97; 95% CI: [1.06, 3.66]) independent of risk factors and diagnosis of whole lung emphysema. Quantitative lobar emphysema improved the goodness-of-fit to lung cancer incidence (, ). We are the first to develop and validate an automated lobe segmentation algorithm that is robust to smoking-related pathology. We discover a quantitative risk factor, lending further evidence that regional emphysema is independently associated with increased lung cancer incidence. The algorithm is provided at https://github.com/MASILab/EmphysemaSeg.

Personalised colorectal cancer screening strategies: Information needs of the target population

Prior faecal Hemoglobin (f-Hb) concentrations of a negative fecal immunochemical test (FIT) can be used for risk stratification in colorectal cancer (CRC) screening. Individuals with higher f-Hb concentrations may benefit from a shorter screening interval (1 year), whereas individuals with undetectable f-Hb concentrations could benefit from a longer screening interval (3 year). Individuals’ views on personalised CRC screening and information needed to make a well-informed decision is unknown. We conducted three semi-structured focus groups among individuals eligible for CRC screening (i.e. men and women aged 55 to 75) in the Netherlands. Thematic analysis was used to analyse participants’ information need on personalised CRC screening strategies. Fourteen individuals took part. The majority were positive about CRC screening and indicated that they would participate in personalised CRC screening. The rationale for a longer interval among those at lowest risk was, however, unclear for many. The preferred information on individual risk was variable: ranging from full information to only information on the personalised strategy without mentioning the risk. It was not possible to address everyone’s need with a single approach. Additional communications, e.g. public media campaigns, billboards, videos on social media, were also suggested as necessary. This study showed that preferences on receiving information on individual CRC risk varied substantially and no consensus was reached. Introducing a personalised screening programme will require careful communication, particularly around the rationale for the strategy, and a layered approach to deliver information.

Views of the Australian public on the delivery of risk-stratified cancer screening in the population: a qualitative study.

Qualitative interview study. We conducted semistructured interviews with participants from a previous study, half of whom had received personal genomic risk information and half of whom had not. We asked how and where they would like to see risk-stratified screening delivered and how they felt about different health professionals assessing their cancer risk. Data were analysed thematically. Forty interviews were conducted. The age range of participants was 21-68 years; 58% were female. Themes included: 1) Convenience is a priority; 2) General practice is a good fit for some; 3) Web-based technology is part of the process; and 4) "I would want to know why [I was being stratified]". Similar views were expressed by both groups. Our findings suggest that although health professionals were identified as having an important role, there were mixed preferences for delivery by general practitioners, medical specialists or nurses. Participants were less concerned about who undertook the risk assessment than whether the health professional had the appropriate skill set and availability. Clear communication and evidence of the need for change in screening eligibility and frequency were key factors in the successful delivery of risk-stratified screening. We identified that convenience and good communication, including clear explanations to the public with convincing evidence for change, will enable the successful delivery of risk-stratified cancer screening in the population, including organised and opportunistic screening approaches. Health professional education and upskilling across disciplines will be key facilitators. Engagement and further consultation with primary care and other key stakeholders will be central.

Resident Esophageal Microbiota Dysbiosis Correlates with Cancer Risk in Barrett's Esophagus Patients and Is Linked to Low Adherence to WCRF/AICR Lifestyle Recommendations.

Esophageal adenocarcinoma (EAC) is the consequence of longstanding gastroesophageal reflux, which leads to inflammation and could cause Barrett's esophagus (BE), the main risk factor for EAC development. The 5 year survival rate of EAC is poor since the diagnosis occurs at the late stage of the disease. To improve patient management, a better comprehension of the mechanism undergoing the evolution through to adenocarcinoma is needed. Within this scenario, the resident microbiome investigation was studied. This study aimed to explore the esophageal microbial profile in patients affected by non-dysplastic BE, low- and high-grade dysplastic BE, and EAC to identify parameters characterizing cancer progression and to develop a score suitable for clinical practice to stratify cancer risk. The microbiota was investigated through the 16S rRNA gene sequencing of esophageal biopsies. The microbial composition was evaluated at each different taxonomic level along the disease progression. To further investigate bacteria potentially associated with cancer development, non-dysplastic and dysplastic/cancer patients were compared. The presence of the six significant microbial features with multivariate analysis was used to develop a multiparametric score (Resident Esophageal Microbial Dysbiosis Test) to predict the risk of progression toward EAC. Finally, the diagnostic ability of the test and its discrimination threshold for its ability to identify dysplastic/cancer patients were demonstrated. Since EAC has been related to obesity, the relationship between these microbial parameters and patients' diet/lifestyle habits was also investigated. Developing microbiome-based risk prediction models for esophageal adenocarcinoma onset could open new research avenues, demonstrating that the resident microbiome may be a valid cancer risk biomarker.