Cancer Epidemic Research Articles

Machine Learning-Guided Differential Gene Expression Analysis Identifies A Highly-Connected Seven-Gene Cluster in Triple-Negative Breast Cancer

Machine Learning-Guided Differential Gene Expression Analysis Identifies A Highly-Connected Seven-Gene Cluster in Triple-Negative Breast Cancer

Pharmacokinetics of Tarlatamab, a Delta-Like Ligand-3 (DLL3) Targeted Half-Life Extended Bispecific T-Cell Engager (BiTE®) Immunotherapy in Adult Patients with Previously Treated Small-Cell Lung Cancer: Results from DeLLphi-300, a Phase I Multiple-Dose-Escalation Study.

Tarlatamab binds to delta-like ligand 3 on cancer cells and cluster of differentiation-3 on T cells, leading to T-cell-mediated tumor lysis, and has demonstrated a promising safety and efficacy profile in patients with previously treated small-cell lung cancer (SCLC). Here, we present pharmacokinetic results from DeLLphi-300 (NCT03319940), an ongoing international, open-label, first-in-human study in previously treated adult patients with SCLC. Multiple escalating doses of tarlatamab were administered every 2 weeks (Q2W; 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30, and 100 mg) in a 28-day cycle. To reduce the risk of cytokine-release syndrome, starting at the 3 mg dose level, a step dose regimen was employed consisting of a 1 mg infusion on cycle 1 day 1 (C1D1), followed by the target dose on C1D8, C1D15, and Q2W thereafter. All doses were infused over 1 h. Other tarlatamab dosing regimens were also explored, either for patient convenience (every 3 weeks) or to mitigate cytokine-release syndrome (extended intravenous infusion over a period of 3 days). Intensive pharmacokinetic samples were collected during cycles 1 and 2, and additional samples for pharmacokinetic and immunogenicity measurement were collected at regular intervals in later cycles. Pharmacokinetic data were analyzed using noncompartmental analysis, and antidrug antibody (ADA) incidence, including any effect on tarlatamab pharmacokinetic parameters, was summarized. Pharmacokinetic data were available from 203 patients. The median age was 62 years (range 32-80), and 55.7% (n = 113) of patients were male, 78.3% (n = 159) were white, and 8.3% (n = 17) were of Japanese descent. Following intravenous infusion, serum tarlatamab concentrations declined with time in a biphasic manner. Serum exposures increased in an approximately dose-proportional manner across the evaluated target dose range with a mean (standard deviation) estimated terminal phase elimination half-life of 5.8 (1.6) days, and steady state achieved by approximately C2D15. Of the 183 evaluable patients, 12 (6.6%) developed treatment-emergent ADAs; the distribution of dose-normalized serum concentrations were similar between patients who were ADA positive and ADA negative. In addition, the distribution of exposures was comparable in Japanese and non-Japanese patients. In patients with previously treated SCLC, tarlatamab demonstrated dose-proportional pharmacokinetic and extended half-life characteristics that support a Q2W dosing interval. Neither Japanese race nor ADA had a clinically relevant impact on exposures.

Application of Zhao Shi Lei-huo-jiu Based on ERAS Concept in Managing Postoperative Gastrointestinal Symptom Cluster in Rectal Cancer

This study explores the application value of Zhao Shi Lei-huo-jiu in managing common postoperative gastrointestinal symptom clusters following rectal cancer surgery, under the framework of the Enhanced Recovery After Surgery (ERAS) concept. By detailing the development, core elements, and application of ERAS in colorectal surgery, combined with the historical origins, unique techniques, and mechanisms of Zhao Shi Lei-huo-jiu, this paper highlights the innovation of integrating traditional Chinese medicine treatments with modern surgical recovery principles. Through a rigorously designed research process, rectal cancer postoperative patients were selected as research subjects, and the data collection and implementation steps were explicitly outlined. The study results provide scientific evidence for the practical efficacy and advantages of Zhao Shi Lei-huo-jiu in postoperative rehabilitation for rectal cancer, offering significant practical implications for guiding clinical practice and promoting early patient recovery.

Application of MRI imaging technology based on magnetic nanoparticles in diagnosis and prognosis evaluation of prostate cancer

Objective: Objective: Prostate cancer is one of the most common malignant tumors in men. Early diagnosis and prognosis evaluation are of great significance for the treatment and prevention of prostate cancer. The purpose of this study was to explore the application of magnetic nanoparticle-based MRI imaging technology in the diagnosis and prognosis assessment of prostate cancer. A total of 81 patients in our hospital from September 2018 to January 2021 were selected as the study objects, all suspected prostate cancer patients, and prostate detection was performed under the guidance of MRI and rectal ultrasound.According to the pathological results, the patients were divided into prostate cancer cluster group and benign prostatic hyperplasia group. Imaging of prostate cancer is achieved by the response of magnetic nanoparticles to magnetic fields. MRI images of patients were collected and analyzed using professional software. It can provide high-resolution images that enable accurate detection and localization of tumors, and the technology can also assess the severity of prostate cancer and predict a patient's prognosis.

Influence of impaired glucose tolerance and type 2 diabetes on the multimorbidity cluster of cardiovascular disease and cancer: a post hoc analysis of the Da Qing Diabetes Prevention Outcome Study

BackgroundThis study explored the influence of type 2 diabetes and impaired glucose tolerance (IGT) on the risk of the multimorbidity cluster of cardiovascular disease (CVD) and cancer.MethodsA total of 1629 participants in the Da Qing Diabetes Prevention Outcome Study were recruited in the present analysis, including normal glucose tolerance (NGT, N = 492), IGT (N = 540), and newly diagnosed type 2 diabetes (N = 597) groups. Cox proportional hazards analyses were performed to assess the relationship between NGT, IGT, and newly diagnosed type 2 diabetes and the risk of the multimorbidity cluster of CVD and cancer.ResultsThe incidence rates for multimorbidity cluster CVD and cancer were 1.25, 3.17, and 3.23 per 1000 person-years in people with NGT, IGT, and the newly diagnosed type 2 diabetes groups, respectively, over 34-year follow-up. Cox analysis revealed that diabetes status (as time-dependent variable) was significantly associated with the subsequent increased risk of multimorbidity cluster of CVD and cancer compared with non-diabetes (hazard ratios [HR] = 2.55, 95% confidence interval [CI] 1.51–4.31) after adjustment of potential confounders. Similar analysis showed that this risk was significantly higher in the IGT and newly diagnosed type 2 diabetes groups compared with NGT, with HR of 3.28 (95% CI 1.83–5.87) and HR of 3.90 (95% CI 2.14–7.09), respectively. Whereas compared diabetes with IGT group, this risk was not significantly different.ConclusionsSimilar to newly diagnosed type 2 diabetes, IGT is significantly associated with an increased risk of the multimorbidity cluster of CVD and cancer compared with NGT. This finding highlights the urgent need for an active detection of IGT and effective prevention and management of diabetes.

Effects of the superior mesenteric artery approach versus the no-touch approach during pancreatoduodenectomy on the mobilization of circulating tumour cells and clusters in pancreatic cancer (CETUPANC): randomized clinical trial.

Patients with pancreatic ductal adenocarcinoma present early postoperative systemic metastases, despite complete oncological resection. The aim of this study was to assess two pancreatoduodenectomy approaches with regard to intraoperative circulating tumour cells and cluster mobilization and their potential association with the development of distant metastasis. Patients with periampullary tumours who underwent open pancreatoduodenectomy were randomly allocated to either the no-touch approach or the superior mesenteric artery approach. A total of four intraoperative portal vein samples (at the beginning of the intervention, after portal vein disconnection from the tumour, after tumour resection, and before abdominal closure) were collected to measure circulating tumour cells and cluster numbers. Primary outcomes were the intraoperative number of circulating tumour cells and cluster mobilization. Further, their potential impact on 3-year distant metastasis disease-free survival and overall survival was assessed. A total of 101 patients with periampullary tumours were randomized (51 in the superior mesenteric artery group and 50 in the no-touch group) and 63 patients with pancreatic ductal adenocarcinoma (34 in the superior mesenteric artery group and 29 in the no-touch group) were analysed. Circulating tumour cells and cluster mobilization were similar in both the no-touch group and the superior mesenteric artery group at all time points. There were no significant differences between surgical groups with regard to the median metastasis disease-free survival (12.4 (interquartile range 6.1-not reached) months in the superior mesenteric artery group and 18.1 (interquartile range 12.1-not reached) months in the no-touch group; P = 0.730). Patients with intraoperative cluster mobilization from the beginning to the end of surgery developed significantly more distant metastases within the first year after surgery (P = 0.023). Two intraoperative factors (the superior mesenteric artery approach (P = 0.025) and vein resection (P < 0.001)) were predictive factors for cluster mobilization. Patients undergoing pancreatoduodenectomy using either the no-touch approach or the superior mesenteric artery approach had similar circulating tumour cells and cluster mobilization and similar overall survival and metastasis disease-free survival. A high intraoperative cluster dissemination during pancreatoduodenectomy was a predictive factor for early metastases in patients with pancreatic ductal adenocarcinoma. NCT03340844 (http://www.clinicaltrials.gov)-CETUPANC trial.

Using the 12-item short-form health survey (SF-12) to evaluate self-rated health in an environmental justice community

The Greater Fifth Ward (GFW) is a Northeast Houston, Texas, neighborhood with a legacy of industrial contamination and a confirmed cancer cluster. To understand self-rated health in the GFW, community-based participatory research (CBPR), was used to promote the inclusion of all partners. CBPR involves the community during each stage of the research process from design to research dissemination. A complete census was conducted, and 114 surveys were obtained in the environmental justice (EJ) community from July to November 2021. EJ communities shoulder an unfair burden of environmental exposures, pollution, and poor built environments. Mental and physical health were measured using the validated 12-item Short Form Health Survey (SF-12v2). We posited that the Black or African American (Black/AA) community would have lower mental composite scores (MCS) and physical composite scores (PCS) compared to the nation and their White counterparts. The MCS and PCS were calculated and compared against the national mean. Overall, participants had higher MCS and lower PCS than the national mean. Black/AA males and females had lower MCS compared to their White counterparts. White females had the lowest PCS among all respondents, significantly lower than the national average. MCS was lower among those who lived in the neighborhood longer. Burdens from pollution may impact residents’ health and perceived health. Targeted interventions or programs that improve mental or physical health would benefit this community and other inequitably burdened neighborhoods.

Pathophysiology of Peritoneal Metastasis.

Peritoneal metastasis is the result of a complex, stepwise process that involves multiple, spatially and temporally distinct interactions between the primary cancer, disseminated cancer cells or clusters, and the mesothelial lining of the peritoneal cavity and intraperitoneal organs. The biology of peritoneal metastasis, long a neglected field of research, is now increasingly being unraveled. Here, we provide an update on the mechanisms that drive the journey that eventually leads to widespread peritoneal metastatic disease.

An Exploration of the Utility and Impacts of Implementation Science Strategies by Cancer Registries for Healthcare Improvement: A Systematic Review.

Cancer data registries are central elements of cancer control programs providing critical insights in measures of performance in cancer healthcare delivery. Evidence to practice gaps in cancer care remain substantial. Implementation science (IS) strategies target gaps between generated research evidence and guideline concordance in delivered healthcare. We performed a systematic review of the utilisation and effectiveness of IS strategies reported by cancer registries. A research protocol and literature search were performed seeking studies incorporating implementation strategies utilised by cancer registries for quality improvement. Searches were undertaken in MEDLINE, Embase, CENTRAL, and the grey literature for randomised trials and observational studies. The "Knowledge to Action" (K2A) framework was used to explore implementation gaps in care delivery. Screening identified 1496 studies, 37 studies identified by title and abstract review, and 9 included for full text review. Studies originated from the United Kingdom, the United States, the Netherlands, and Australia reporting on lung, breast, colo-rectal, and cancer clusters. Registry jurisdictions included 7 national, 4 state, and 4 local registries. Knowledge gap analysis consistently identified monitoring and evaluation of data outcomes in accord with registry primary purpose although limited exploration of the utilisation, translation and re-application of this data. Studies lacked description of strategies describing sustainability of generated knowledge, identification of barriers, knowledge adaptation to local contexts, and the selection, adaptation and implementation of interventions for improvement. Available studies provide limited literature evidence of the effective utilisation of IS strategies reported by cancer registries for healthcare improvement. A substantial opportunity presents to study the engagement of IS in cancer registry data use to close the evidence practice gap and facilitate data driven improvement in cancer healthcare.

Abstract A057: Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020

Abstract Introduction: Living within proximity to hazardous waste (superfund) sites can pose an increased risk of exposure to chemicals of concern, including cancerogenic substances. Per- square mile, Puerto Rico has a high density of contaminated sites, including the designation of 19 superfund sites by the Environmental Protection Agency across the archipelago. Understanding how living within proximity to superfund sites can help recognize communities that are at greater health risks, such as increased cancer risks. Objectives: Identify clusters and outliers for all types of cancer, to assess ecological risk, by the presence of superfund sites across Puerto Rico. Methods: All types of cancer were recorded and provided by the Puerto Rico Central Cancer Registry for the period of 2010-2020. This data was summarized by municipalities (n=78). Cancer cases in each county were aggregated and divided by population in 2020 to show prevalence of cases. Using geographical information systems (ArcGIS), a Local Moran’s I was run to identify potential municipalities that have clusters; location with similar high (hot spots) or low values (cold spots) and outliers; locations with dissimilar values from their surrounding neighbors. A layer representing municipalities with superfund sites was also applied to the map to see if there was a relationship between living in a superfund site and cancer risk. This study was approved by UPRCCC IRB Protocol #2023-11-124. Results: Between 2010 and 2020, a total of 114,560 diagnosis occurred for all types of cancer in PR, from which 48.06% accounted for females and 51.93% for males, with breast and prostate as the primary cancer sites, respectively. Our analyses showed one hotspot and three cold spots with statistically significant differences from their neighboring municipalities. One hotspot was in Canovanas (p=0.03) which has a superfund site related to pharmaceutical chemicals. The three coldspots were in Cataño (p=0.04), Trujillo Alto (p=0.04), and Guánica (p=0.03). Additionally, four high and low outliers were identified. Across the municipalities, in the lower outliers Vega Alta (p=0.04), Corozal (p=0.002) are the only ones with current Superfund sites. Cabo Rojo (p=0.002) and San German (p=0.006) are included in the list of higher outliers, which are places with superfund sites. However, Hormigueros (p=0.03), and Arroyo (p=0.03), are also in this category. Conclusion: The results identify the key cancer clusters and outliers across municipalities in comparison to neighboring municipalities on the island. Results show municipalities with and without Superfund sites as part of the higher outliers list, which additional research could help establish other contributing factors. Further analysis is needed to consider what factors affect the clusters such as age range, type of cancer, and presence of other environmental contaminants in the area. Acknowledgements: This research was supported by award 1R25CA240120-01 (Cancer Prevention &amp; Control Research Training Program) from the National Cancer Institute. Citation Format: Sailing JT Tang, Nancy R. Cardona, Ana P. Ortiz. Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020 [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A057.

Growth pattern of de novo small clusters of colorectal cancer is regulated by Notch signaling at detachment.

Cancer cell clusters have a higher capacity for metastasis than single cells, suggesting cancer cell clusters have biological properties different from those of single cells. The nature of de novo cancer cell clusters that are newly formed from tumor masses is largely unknown. Herein, we generated small cell clusters from colorectal cancer organoids and tracked the growth patterns of the clusters up to four cells. Growth patterns were classified into actively growing and poorly growing spheroids (PG). Notch signaling was robustly activated in small clusters immediately after dissociation, and Notch signaling inhibition markedly increased the proportion of PG spheroids. Only a limited number of PG spheroids grew under growth-permissive conditions invitro, but xenograft tumors derived from Notch inhibited clusters showed growth rates comparable to those of untreated spheroids. Thus, de novo clusters are composed of cells with interchangeable growth fates, which are regulated in a context-dependent manner by Notch signaling.

Identifying patterns of co-occurring chronic conditions preceding dementia: An unsupervised machine learning approach using health administrative data

ObjectivesIndividual risk factors for dementia are well known, but the influence of co-occurring chronic conditions has not been considered. We identified clusters of chronic conditions using an unsupervised machine learning approach and examined associations with incident dementia. ApproachUsing linked population-based administrative databases, we followed all community-dwelling adults aged 40-54 years in Ontario, Canada from April 2002 until March 2019 for incident dementia. We estimated the prevalence of 29 chronic conditions using validated algorithms and/or diagnosis codes. We reduced dataset dimensionality using multiple correspondence analysis and a fuzzy c-means clustering algorithm identified the optimal number of clusters (between 3-6 tested). Associations between clusters and incident dementia were examined using a cause-specific hazard model adjusted for sociodemographic characteristics and accounting for the competing risk of death. ResultsWe identified 82,359 eligible individuals (random 3% sample of total eligible individuals; mean age 46.5 years; 50.4% female). Regression analyses were based on 5 comorbidity clusters (fuzzy silhouette index:0.69). Compared to the low comorbidity cluster, persons in the cerebrovascular disease/metabolic (HRadj=3.06, 95%CI[2.42,3.86]) and neuro-related/mental health clusters (HRadj=2.51, 95%CI[2.05,3.07]) had the highest rates of incident dementia, followed by the cardiovascular risk factor cluster (HRadj=1.66,95%CI[1.32,2.09]). Persons in the cancer cluster did not have an increased incidence of dementia (HRadj=0.96,95%CI[0.77,1.20]). ConclusionsWe found significant associations between machine learning-derived clusters of chronic conditions and dementia. ImplicationsUnsupervised machine learning approaches to identify clusters of chronic conditions may be a useful tool for considering the impact of multimorbidity on dementia risk.

Sharp approximation and hitting times for stochastic invasion processes

We are interested in the invasion phase for stochastic processes with interactions. A single mutant with positive fitness arrives in a large resident population at equilibrium. By a now classical approach, the first stage of the invasion is well approximated by a branching process. The macroscopic phase, when the mutant population is of the same order as the resident population, is described by the limiting dynamical system. We capture the intermediate mesoscopic phase for the invasive population and obtain sharp approximations. It allows us to describe the fluctuations of the hitting times of thresholds, which inherit a large variance from the first stage. We apply our results to two models which are original motivations. In particular, we quantify the hitting times of critical values in cancer emergence and epidemics.

Spatial and temporal distribution characteristics research of esophageal cancer in China

Objectives: To explore the spatial distribution characteristics, trend changes, and spatial clustering of esophageal cancer among residents in China at the county (city, district) scale, a spatial epidemiological approach was used, with the aim of providing localized evidence for the prevention and treatment of esophageal cancer in China. Methods: The data source was the incidence (crude rate) and mortality (crude rate) of esophageal cancer from 2005 to 2016 in the 2008-2019 edition of China Cancer Registration Annual Report published by the National Cancer Center. The Joinpoint model was used for time trend analysis. The tumor registration area in 2016 was selected as the study area for spatial feature analysis, with a total of 487 counties (cities and districts), covering 27.6% of the national population. Spatial autocorrelation analysis was performed to reveal spatial distribution characteristics by using Arcgis 10.6 software, and spatial scanning statistics was used to analyze spatial clustering characteristics by using SaTScan 9.5 software. The log-likelihood ratio (LLR) and relative risk (RR) were calculated in different windows, and the region with the largest LLR value represented the most likely cluster. Results: From 2005 to 2016, the incidence and mortality rate of esophageal cancer in China showed a trend of increasing at first and then decreasing. The incidence and mortality rate of esophageal cancer in 2016 were characterized by spatial positive correlation. High incidence and high mortality were mainly concentrated in the areas through which the Huaihe River flowed. The primary clusters (taking high incidence rate as an example LLR=6 374.41, RR=2.37, P＜0.001) were mainly distributed in Jiangsu, Anhui and Shandong in eastern China and eastern Henan and southern Hebei in central China, and secondary clusters (taking high incidence rate as an example LLR=1 971.19, RR=1.91, P＜0.001) in Gansu, Ningxia Hui Autonomous Region, Shaanxi, Sichuan and other central and western regions. Conclusions: The incidence and mortality of esophageal cancer in China have decreased since 2010. The disease burden of esophageal cancer has obvious spatial differences, and measures should be taken according to local conditions in high-risk cluster areas such as the Huaihe River basin.

Pairwise-Constraint-Guided Multi-View Feature Selection by Joint Sparse Regularization and Similarity Learning

Feature selection is a basic and important step in real applications, such as face recognition and image segmentation. In this paper, we propose a new weakly supervised multi-view feature selection method by utilizing pairwise constraints, i.e., the pairwise constraint-guided multi-view feature selection (PCFS for short) method. In this method, linear projections of all views and a consistent similarity graph with pairwise constraints are jointly optimized to learning discriminative projections. Meanwhile, the l2,0-norm-based row sparsity constraint is imposed on the concatenation of projections for discriminative feature selection. Then, an iterative algorithm with theoretically guaranteed convergence is developed for the optimization of PCFS. The performance of the proposed PCFS method was evaluated by comprehensive experiments on six benchmark datasets and applications on cancer clustering. The experimental results demonstrate that PCFS exhibited competitive performance in feature selection in comparison with related models.

Symptom network and quality of life of breast cancer patients receiving multimodal cancer treatment: Cross-sectional study

PurposeBreast cancer patients experience symptoms and side effects from multimodal treatments, which often include menopausal symptoms resulting from cytotoxic chemotherapy or estrogen suppression therapy. This study aimed to explore the symptom network and clusters and its relationship to quality of life (QoL) in breast cancer patients who receive multimodal cancer treatment and experience treatment-related menopausal symptoms. MethodsA correlational study was conducted. Breast cancer patients receiving multimodal cancer treatment and experiencing treatment-related menopausal symptoms were included while they were receiving radiation therapy (N = 250). Symptoms, functions and QoL were assessed using the EORTC QLQ-C30 and BR45. Network analysis, principal component analysis, exploratory factor analysis, and multiple linear regression analysis were conducted. ResultsFatigue was the most central symptom in the symptom-only network as well as in the network consisting of symptoms and QoL. Fatigue, systemic therapy side effects, appetite loss, and cognitive symptoms demonstrated significant associations with QoL. The cancer and treatment related symptom cluster consisted of fatigue, cognitive symptoms, emotional symptoms and systemic therapy side effects. Breast cancer therapy-specific symptoms, such as arm symptoms, skin mucosis symptoms, and breast symptoms, formed a cluster with pain. ConclusionFatigue was the most central symptom in breast cancer patients receiving multimodal cancer treatment and experiencing menopausal symptoms. Evaluation of fatigue and providing interventions to manage fatigue would contribute to improvement of QoL of breast cancer patients receiving multimodal cancer treatments. Future network analysis and symptom cluster studies should specify the population of interest and the treatment phase using comprehensive symptom evaluation tools.

Association of latent class analysis-derived multimorbidity clusters with adverse health outcomes in patients with multiple long-term conditions: comparative results across three UK cohorts

It remains unclear how to meaningfully classify people living with multimorbidity (multiple long-term conditions (MLTCs)), beyond counting the number of conditions. This paper aims to identify clusters of MLTCs in different age groups and associated risks of adverse health outcomes and service use. Latent class analysis was used to identify MLTCs clusters in different age groups in three cohorts: Secure Anonymised Information Linkage Databank (SAIL) (n=1,825,289), UK Biobank (n=502,363), and the UK Household Longitudinal Study (UKHLS) (n=49,186). Incidence rate ratios (IRR) for MLTC clusters were computed for: all-cause mortality, hospitalisations, and general practice (GP) use over 10 years, using <2 MLTCs as reference. Information on health outcomes and service use were extracted for a ten year follow up period (between 01st Jan 2010 and 31st Dec 2019 for UK Biobank and UKHLS, and between 01st Jan 2011 and 31st Dec 2020 for SAIL). Clustering MLTCs produced largely similar results across different age groups and cohorts. MLTC clusters had distinct associations with health outcomes and service use after accounting for LTC counts, in fully adjusted models. The largest associations with mortality, hospitalisations and GP use in SAIL were observed for the "Pain+" cluster in the age-group 18-36 years (mortality IRR=4.47, hospitalisation IRR=1.84; GP use IRR=2.87) and the "Hypertension, Diabetes & Heart disease" cluster in the age-group 37-54 years (mortality IRR=4.52, hospitalisation IRR=1.53, GP use IRR=2.36). In UK Biobank, the "Cancer, Thyroid disease & Rheumatoid arthritis" cluster in the age group 37-54 years had the largest association with mortality (IRR=2.47). Cardiometabolic clusters across all age groups, pain/mental health clusters in younger groups, and cancer and pulmonary related clusters in older age groups had higher risk for all outcomes. In UKHLS, MLTC clusters were not significantly associated with higher risk of adverse outcomes, except for the hospitalisation in the age-group 18-36 years. Personalising care around MLTC clusters that have higher risk of adverse outcomes may have important implications for practice (in relation to secondary prevention), policy (with allocation of health care resources), and research (intervention development and targeting), for people living with MLTCs. This study was funded by the National Institute for Health and Care Research (NIHR; Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (multimorbidity)-NIHR202020).

Heavy-metal associated breast cancer and colorectal cancer hot spots and their demographic and socioeconomic characteristics.

Cancer registries offer an avenue to identify cancer clusters across large populations and efficiently examine potential environmental harms affecting cancer. The role of known metal carcinogens (i.e., cadmium, arsenic, nickel, chromium(VI)) in breast and colorectal carcinogenesis is largely unknown. Historically marginalized communities are disproportionately exposed to metals, which could explain cancer disparities. We examined area-based metal exposures and odds of residing in breast and colorectal cancer hotspots utilizing state tumor registry data and described the characteristics of those living in heavy metal-associated cancer hotspots. Breast and colorectal cancer hotspots were mapped across Kentucky, and area-based ambient metal exposure to cadmium, arsenic, nickel, and chromium(VI) were extracted from the 2014 National Air Toxics Assessment for Kentucky census tracts.Among colorectal cancer (n = 56,598) and female breast cancer (n = 77,637) diagnoses in Kentucky, we used logistic regression models to estimate Odds Ratios (ORs) and 95% Confidence Intervals to examine the association between ambient metal concentrations and odds of residing in cancer hotspots, independent of individual-level and neighborhood risk factors. Higher ambient metal exposures were associated with higher odds of residing in breast and colorectal cancer hotspots. Populations in breast and colorectal cancer hotspots were disproportionately Black and had markers of lower socioeconomic status. Furthermore, adjusting for age, race, tobacco and neighborhood factors did not significantly change cancer hotspot ORs for ambient metal exposures analyzed. Ambient metal exposures contribute to higher cancer rates in certain geographic areas that are largely composed of marginalized populations. Individual-level assessments of metal exposures and cancer disparities are needed.

Identification of disulfidptosis-related clusters and construction of a disulfidptosis-related gene prognostic signature in triple-negative breast cancer

ObjectiveThis study aimed to explore disulfidptosis-related clusters of triple-negative breast cancer (TNBC) and build a reliable disulfidptosis-related gene signature for forecasting TNBC prognosis. MethodsThe disulfidptosis-related clusters of TNBC were identified based on public datasets, and a comparative analysis was conducted to assess their differences in the overall survival (OS) and immune cell infiltration. Morever, the differentially expressed genes (DEGs) between clusters were recognized. Then, the prognostic DEGs were then chosen. A prognostic signature was constructed by the prognostic DEGs, followed by nomogram construction, drug sensitivity, immune correlation, immunotherapy response prediction, and cluster association analyses. ResultsTwo disulfidptosis-related clusters of TNBC were identified, which had different OS and macrophage infiltration. Moreover, 235 DEGs were identified between two clusters. A prognostic signature was then constructed by five prognostic DEGs including HLA-DQA2, CCL13, GBP1, LAMP3, and SLC7A11. This signature was highly valuable in predicting prognosis. A nomogram was built by risk score and AJCC stage, which could forecast OS accurately. Moreover, patients with high-risk scores exhibited greater sensitivity to chemotherapy drugs such as lapatinib and had a lower immunotherapy response. ConclusionsTwo TNBC clusters linked to disulfidptosis were identified, with different OS and immune cell infiltration. Moreover, a five-disulfidptosis-related gene signature may be a powerful prognostic biomarker for TNBC.

Subclonal mutational signatures in breast cancer brain metastases.

e13108 Background: Breast cancer is the leading cause of cancer-related deaths among women in Brazil and the cancer type with highest incidence. When diagnosed at early stages, it has an overall five-year survival rate of up to 90%. However, in advanced stages, survival rate is reduced to about 24%, and 90% of women in stage IV die of metastatic complications. Brain is one of the most common metastatic sites in breast cancer patients, and even though it is a site with poor prognosis, the mutational profile of brain tumors is poorly described in the literature. Therefore, we understand that the identification of this profile may contribute to elucidate mechanisms associated with tumor progression. The aim of this study was to reconstruct the subclonal evolution of breast cancer metastases in the brain. Methods: To carry out this study, the whole exome was accessed through Next Generation Sequencing (NGS) using the Illumina platform in DNA samples extracted from buffy coat cryopreserved and paraffin material of breast tumors and paired brain metastases (n=10). The median read coverage was 68x. DNA was aligned to a Human Reference Genome using the Burrows–Wheeler Aligner, Genome Analysis Toolkit was used for germline short variants calling, and Mutect2 and MuSE were used for variant calling with somatic character (SNVs and INDELs). FACETS was used for assessing the somatic DNA copy number (Copy Number Aberrations). PyClone-VI tool was used for the subclonal reconstruction and to infer the phylogeny it was considered the mutation loci, Cancer Cell Fraction (CCF) and clustering assignments, using R Statistical Environment and Stats, Argparse, and Devtools packages. Results: We identified the mutational signature in these patients with subclonal and clonal mutations that segregated in approximately two clusters with a median between ten and forty variants related with tumor progression process. Conclusions: These findings show a set of variants with driver potential for breast cancer brain metastasis, bringing new perspectives in identifying mechanisms associated with disease progression.