Improve Cancer Prognosis Research Articles

Electronic consultation from primary care to a cardiology department improves outcomes in patients with cancer

Abstract Background The number of cancer patients with known cardiovascular (CV) disease is increasing due to improved cancer prognosis. Purpose The objective of this study is to assess the long-term results of cancer patients referred to a cardiology department by primary care using electronic consultation (e-consultation). Methods We analysed the patients with previous diagnosis of cancer referred to a cardiology department (CD) from 2010 to 2021 (n=6.889), selected from a total of 68.518 patients (61.629 without cancer), and compared two assistance models: in-person practice (from 2010 to 2012) and e-consultation (from 2013 to 2021). In the first period, all the patients referred by primary care physicians (PCPs) were seen in an in-person consultation and in the e-consultation model the cardiologist reviewed the electronic records (e-consultation) and decided to solve without any visit or, if it was necessary, with an in-person consultation. The outcomes between both periods were analysed using an interrupted time series regression model: 1) delay time to cardiology assistance; 2) all-cause and cardiovascular hospital admissions, and 3) all-cause and cardiovascular mortality during the first year after the initial consultation or e-consultation to the CD. Results Among cancer patients referred to cardiology consultation, the introduction of e-consultation decreased waiting times to cardiology care by 51,8% (95% CI: 51,7%-51,9%) (Fig 1). Over 60% of referrals were resolved in less than 8 days, with this proportion significantly higher after the e-consultation program was introduced (p<0,001). Furthermore, we observed a reduction in the one-year rate of outcomes, with an incidence rate ratio (iRR) [IC 95%] of 0,75 [0,73-0,77] for CV-related hospitalizations (Fig 2b), 0,43 [0,42-0,44] for all-cause hospitalization (Fig 2a), and 0,87 [0,86-0,88] for all-cause mortality. In the multivariate analysis, the delay in receiving cardiology care was significantly associated with an independent increase in 1-year mortality (OR [95% CI] 1,39 [1,06-1,83]) and hospital admission (OR [95% CI] 1,25 [1,02-1,52]). Furthermore, the implementation of the e-consult model was associated with a reduction in hospital admission rates (OR [95% CI] 0,19 [0,14-0,25]). Conclusions In comparison to the in-person consultation period, an outpatient care program that incorporates e-consultation for cancer patients significantly reduced waiting times for cardiology care and shown to be safe, associated with lower rates of hospital admissions.Figure 1Figure 2

Abstract A074: Racial-Ethnic Disparities in Cancer Survival and Stages: A Focus on South Asian Americans

Abstract Introduction: Studying racial-ethnic disparities in cancer risk helps to understand the causes and develop targeted screening and education strategies. South Asian Americans (SAA) are a fast- growing ethnic group in the US,but there is limited research on their cancer risks and outcomes.This study examines overall survival and cancer stage distribution patterns among SAA in comparison to other ethnic groups to highlight disparities in cancer risk and outcomes.Method: We analyzed cancer incidence in 34,552 South Asian patients diagnosed with 23 cancer types between 2000 and 2018 using 18 SEER registries. Using the R package MatchIt, 34,552 White patients were matched based on age, sex,income,rural/urban code,marital status,diagnosis year,and cancer type from 5,106,999 White patients. Overall survival was estimated using the Kaplan-Meier method, and log-rank p-values were reported. Statistical summaries included mean, standard deviation, and percentage. T-tests or Chi-Square tests were used where applicable. A p-value < 0.05 was considered significant. All analyses were performed in R version 4.2.2 using survival, survminer, and tableone packages. Results: SAA population exhibited a median survival of 195 months (95% CI: -188 to 201). Asian-Pacific Islanders (API) had a median survival of 184 months (95% CI: -179 to 191, p < 0.0001).Whites median survival was 152 months (95% CI: -147 to 158, p < 0.0001). Hispanics showed a median survival of 153 months (95% CI: -147 to 159, p < 0.0001). Black population had the lowest median survival of 116 months (95% CI: -112 to 120, p < 0.0001). Regarding disease stages, the SAA population had 21.8% distant stage,1.3% in in-situ stage,38.0% localized stage,21.1% regional stage,17.8% unknown stage.In contrast,API had 20.8% distant stage,3.2% in situ stage,37.6% localized stage, 20.9% regional stage,17.6% in unknown stage. White population showed 19.5% in distant stage,7.4% in in situ stage,35.2% in localized stage,20.1% in regional stage,17.8% in unknown stage. Hispanics had 20.9% distant stage,3.4% in situ stage,36.1% localized stage, 20.8% regional stage, 18.8% unknown stage. Black population presented with 22.2% distant stage,2.1% in situ stage,37.9% localized stage,19.4% regional stage,18.4% unknown stage. Discussion: Our study reveals significant disparities in overall survival and disease stage distribution among different ethnic groups. SAA exhibit the highest median survival but also a high proportion of advanced-stage diagnoses, highlighting the need for improved early detection and screening tailored to this population. The Black population, with the lowest median survival, underscores critical gaps in healthcare access that require urgent attention. Variations in disease stage at diagnosis among White, Hispanic, API, and SAA populations emphasize the importance of culturally sensitive healthcare interventions and equitable resource allocation. These findings advocate for targeted strategies to address the needs of each ethnic group, aiming to reduce disparities and improve cancer prognosis for all. Citation Format: Jasmin Hundal, Sudhipto Mukherjee, Abhay Singh, Yanwen Chen. Racial-Ethnic Disparities in Cancer Survival and Stages: A Focus on South Asian Americans [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 A074.

Consensus document on the implications of standardization of BCG supply in the management of patients with non-muscle-invasive bladder cancer

Patients with non-muscle-invasive bladder cancer (NMIBC) in the intermediate and high-risk groups must receive adjuvant treatment with intravesical Bacillus Calmette–Guérin (BCG) following transurethral resection (TUR), as it reduces the risk of recurrence and presumably the risk of progression as well. Optimization of BCG efficacy is achieved by administering maintenance therapy. However, since many immunological aspects of the mechanism of action of BCG in the bladder remain unknown, the implementation of the optimal dose, number of instillations, strains and adequate maintenance regimen over the last decades has been heterogeneous. Additionally, this has hindered the interpretation of efficacy in terms of oncologic outcomes. This, together with the shortages of BCG in recent years, have forced scientific societies to adapt their clinical practice guidelines and modify their protocols of adjuvant treatment with BCG. This includes changes to strains, doses, and maintenance during this period of time. This consensus document evaluates the current status of adjuvant BCG treatment and the implications of BCG supply availability in the treatment of patients with NMIBC. It also addresses the implementation of novel therapies that will improve cancer prognosis and the quality of life of patients with NMIBC in the future.

Non-canonical olfactory pathway activation induces cell fusion of cervical cancer cells

Multinucleation occurs in various types of advanced cancers and contributes to their malignant characteristics, including anticancer drug resistance. Therefore, inhibiting multinucleation can improve cancer prognosis; however, the molecular mechanisms underlying multinucleation remain elusive. Here, we introduced a genetic mutation in cervical cancer cells to induce cell fusion-mediated multinucleation. The olfactory receptor OR1N2 was heterozygously mutated in these fused cells; the same OR1N2 mutation was detected in multinucleated cells from clinical cervical cancer specimens. The mutation-induced structural change in the OR1N2 protein activated protein kinase A (PKA), which, in turn, mediated the non-canonical olfactory pathway. PKA phosphorylated and activated furin protease, resulting in the cleavage of the fusogenic protein syncytin-1. Because this cleaved form of syncytin-1, processed by furin, participates in cell fusion, furin inhibitors could suppress multinucleation and reduce surviving cell numbers after anticancer drug treatment. The improved anticancer drug efficacy indicates a promising therapeutic approach for advanced cervical cancers.

Documento de consenso sobre las implicaciones de la normalización del suministro del Bacillus Calmette-Guérin en el manejo del paciente con tumor vesical no-músculo invasivo (TVNMI)

Patients with non-muscle-invasive bladder cancer (NMIBC) in the intermediate and high-risk groups must receive adjuvant treatment with intravesical Bacillus Calmette-Guerin (BCG) following transurethral resection (TUR), as it reduces the risk of recurrence and presumably the risk of progression as well. Optimization of BCG efficacy is achieved by administering maintenance therapy. However, since many immunological aspects of the mechanism of action of BCG in the bladder remain unknown, the implementation of the optimal dose, number of instillations, strains and adequate maintenance regimen over the last decades has been heterogeneous. Additionally, this has hindered the interpretation of efficacy in terms of oncologic outcomes. This, together with the shortages of BCG in recent years, have forced scientific societies to adapt their clinical practice guidelines and modify their protocols of adjuvant treatment with BCG. This includes changes to strains, doses, and maintenance during this period of time. This consensus document evaluates the current status of adjuvant BCG treatment and the implications of BCG supply availability in the treatment of patients with NMIBC. It also addresses the implementation of novel therapies that will improve cancer prognosis and the quality of life of patients with NMIBC in the future.

A novel conditional survival nomogram for monitoring real-time prognosis of non-metastatic colorectal cancer

AimsThe aim of this study is to enhance the accuracy of monitoring and treatment information for patients diagnosed with colorectal cancer (CRC).MethodsUtilizing the Surveillance, Epidemiology, and End Results (SEER) database, a cohort of 335,948 eligible CRC patients was included in this investigation. Conditional survival probability and actuarial overall survival were employed as methodologies to investigate the association between clinicopathological characteristics and cancer prognosis.ResultsAmong CRC patients, the 5-year survival rate was 59%, while the 10-year survival rate was 42%. Over time, conditional survival showed a consistent increase, with rates reaching 45% and 48% for individuals surviving 1 and 2 years, respectively. Notably, patients with unfavorable tumor stages exhibited substantial improvements in conditional survival, thereby narrowing the disparity with actuarial overall survival over time.ConclusionThis study underscores the significance of time-dependent conditional survival probability, particularly for patients with a poorer prognosis. The findings suggest that long-term CRC survivors may experience improved cancer prognosis over time.

Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system

Spatial transcriptomics (ST) provides insights into the tumor microenvironment (TME), which is closely associated with cancer prognosis, but ST has limited clinical availability. In this study, we provide a powerful deep learning system to augment TME information based on histological images for patients without ST data, thereby empowering precise cancer prognosis. The system provides two connections to bridge existing gaps. The first is the integrated graph and image deep learning (IGI-DL) model, which predicts ST expression based on histological images with a 0.171 increase in mean correlation across three cancer types compared with five existing methods. The second connection is the cancer prognosis prediction model, based on TME depicted by spatial gene expression. Our survival model, using graphs with predicted ST features, achieves superior accuracy with a concordance index of 0.747 and 0.725 for The Cancer Genome Atlas breast cancer and colorectal cancer cohorts, outperforming other survival models. For the external Molecular and Cellular Oncologycolorectal cancer cohort, our survival model maintains a stable advantage.

Evaluating the effect of a mobile-based symptom monitoring system for improving physical function in patients with cancer during chemotherapy: study protocol for a multicentre randomised controlled trial

IntroductionSymptoms due to chemotherapy are common in patients with cancer. Cancer-related symptoms are closely associated with the deterioration of physical function which can be associated with decreased quality of life...

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types.

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

Effects of immune checkpoint inhibitor associated endocrinopathies on cancer survival.

Immune checkpoint inhibitors (ICIs) are associated with immune-related adverse events (irAEs), of which endocrinopathies are common. We characterized endocrine and non-endocrine irAEs in cancer patients receiving ICIs, identified risk factors for their development and established whether endocrine and non-endocrine irAEs were differentially associated with improved cancer prognosis. Single-center, retrospective cohort study of patients with advanced or metastatic solid tumors receiving at least one ICI treatment cycle (242 men, 151 women, median age 65 years). Main outcome measures were incidence of any irAE during the study period, overall survival and time to treatment failure. Non-endocrine irAEs occurred in 32% and endocrine irAEs in 12% of patients. Primary thyroid dysfunction was the most common endocrine irAE (9.5%) and the majority of endocrinopathies required permanent hormone replacement. Women had an increased risk of developing endocrine irAEs (p = 0.017). The biggest survival advantage occurred in patients who developed both endocrine and non-endocrine irAEs (overall survival: HR 0.16, CI 0.09-0.28). Time to treatment failure was also significantly improved in patients who developed endocrine irAEs (HR 0.49, CI 0.34 - 0.71) or both (HR 0.41, CI 0.25 - 0.64) but not in those who only developed non-endocrine irAEs. Women may have increased risk of endocrine irAEs secondary to ICI treatment. This is the first study to compare the effects of endocrine irAEs with non-endocrine irAEs on survival. Development of endocrine irAEs may confer survival benefit in ICI treatment and future, prospective studies are needed to elucidate this.

Inhibiting Pathological Calcium Phosphate Mineralization: Implications for Disease Progression.

Pathological calcifications, especially calcium phosphate microcalcifications (MCs), appear in most early breast cancer lesions, and their formation correlates with more aggressive tumors and a poorer prognosis. Hydroxyapatite (HA) is a key MC component that crystallizes in the tumor microenvironment. It is often associated with malignant breast cancer lesions and can trigger tumorigenesis in vitro. Here, we investigate the impact of additives on HA crystallization and inhibition, and how precancerous breast cells respond to minerals that are deposited in the presence of these additives. We show that nonstoichiometric HA spontaneously crystallizes in a solution simulating the tumor microenvironmental fluids and exhibits lump-like morphology similar to breast cancer MCs. In this system, the effectiveness of poly(aspartic acid) and poly(acrylic acid) (PAA) to inhibit HA is examined as a potential route to improve cancer prognosis. In the presence of additives, the formation of HA lumps is associated with the promotion or only minimal inhibition of mineralization, whereas the formation of amorphous calcium phosphate (ACP) lumps is followed by inhibition of mineralization. PAA emerges as a robust HA inhibitor by forming spherical ACP particles. When precancerous breast cells are exposed to various HA and ACP minerals, the most influential factors on cell proliferation are the mineral phase and whether the mineral is in the form of discrete particles or particle aggregates. The tumorigenic effects on cells, ranging from cytotoxicity and suppression of proliferation to triggering of proliferation, can be summarized as HA particles < HA aggregates < ACP particles < ACP aggregates. The cellular response to minerals can be attributed to a combination of factors, including mineral phase, crystallinity, morphology, surface texture, aggregation state, and surface potential. These findings have implications for understanding mineral-cell interactions within the tumor microenvironment and suggest that, in some cases, the byproducts of HA inhibition can contribute to disease progression more than HA itself.

Abstract 993: Comprehensive immunophenotypic strategies to enable equity in remote settings for improved cancer prognosis

Abstract Improved cancer prognosis begins with insights obtained from high quality data during clinical trials. Execution of longitudinal clinical trials in flow cytometry is complex, primarily due to logistical challenges in high quality sample collection. For instance, highly remote indigenous population centers are both disadvantaged in access to healthcare and often underrepresented in clinical trials. This paradox is highlighted in the case of Australian First Nations communities, for which lung cancer prevalence peaks in males at twice the magnitude of the general population. Our group has developed a novel blood “immune signature” that robustly predicts failure to make a clinical response to checkpoint therapies targeting the PD-1/PD-L1 pathway. Encouraged by these groundbreaking findings, which were achieved through applying a comprehensive 38-plex immunophenotyping CyTOF panel to biobanked cancer samples, recent advances in CyTOF technology now give us the opportunity to expand our clinical implementation to remote settings, with a further expanded panel to 50+ markers. CyTOF is the only technology that allows easily implemented remote asynchronous sample collection and the largest immunophenotyping panel that yields reproducible results. Asynchronous collection is uniquely enabled using a stable lyophilized large-scale staining panel and achieving comprehensive marker coverage in one panel minimizes blood sample required. Furthermore, the new technology enables a highly simplified workflow including blood collection and processing in remote locations to enable the simplest clinical trial infrastructure complexity and cost, easily implemented in current hospital lab environments. As such, this study is designed to ultimately demonstrate both clinical impact of the large panel and utility of CyTOF technology for highly simplified and robust workflow for multi-site clinical trials. This project has 3 phases; i) implementation and evaluation of the collection, analysis technique and data management of this new approach across multiple sites, ii) collection of samples for analysis both pre- and post- initiation of therapy to establish efficacy and optimize as necessary, and iii) blinded clinical trial. We will report on the first phase of this project which is implementing new workflow across clinical collection site, data integration and analysis. This workflow would enable highly simplified collection to access indigenous and under-served populations spread across remote sites in Australia. Citation Format: Natalie J. Smith, Michael Cohen, Julie Alipaz, Christina Loh, David King, Barbara Fazekas de St Groth, Helen M. McGuire. Comprehensive immunophenotypic strategies to enable equity in remote settings for improved cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 993.

Short-term efficacy of oxaliplatin as interventional therapy for liver cancer, and its effect on serum CD163 and AFU

Purpose: To investigate the short-term effectiveness of oxaliplatin in the interventional treatment of liver cancer, and its effect on serum CD163 and α-L-glucosidase (AFU). &#x0D; Methods: Eighty liver carcinoma patients treated in The Affiliated Hospital of Shaoxing University, Shaoxing, China from January 2022 to January 2023 were allotted to 2 cohorts (each with 40 patients). Subjects in control group were treated with hepatic Transarterial Chemoembolization (TACE), while study group was treated with combination of hepatic TACE and oxaliplatin. Efficacy, serological indicators, health status and cancer-related fatigue were determined and compared between both cohorts. &#x0D; Results: DCR was significantly higher in study group than in the control. There were significantly reduced post-treatment amounts of CYFRA21-1, CA125 and VGEF in the study cohort, relative to pre-treatment and control levels (p &lt; 0.05). Post-treatment values of CD4+/CD8+ and CD4+ were significantly low, relative to levels before treatment, while CD8+ in both groups were significantly increased after treatment (p &lt; 0.05). However, post-treatment T lymphocyte level was comparable in both groups. There was significantly higher post-treatment KPS score in study cohort than pre-treatment and control scores, but RPFS score was significantly reduced, relative to the corresponding pre-treatment and control scores. Post-treatment serum amounts of CD163 and AFU were significantly down-regulated in both cohorts, with lower levels in the study cohort. &#x0D; Conclusion: The combined use of liver TACE and oxaliplatin produces good clinical outcome in the treatment of liver cancer. It is beneficial in reducing serum levels of CD163 and AFU, inhibits proliferation of tumor cells, reduces tumor volume, and improves cancer prognosis in patients.

Microtubule interacting and trafficking domain containing 1 deficiency leads to poor survival via tissue factor-mediated coagulation in bladder cancer

BackgroundPatients with cancer are at an increased risk of developing a hypercoagulative phenotype and venous thromboembolism. However, no clinical trial has yet confirmed that anticoagulant therapy improves cancer prognosis, and the mechanism underlying hypercoagulation in patients with bladder cancer is not well understood. ObjectivesWe hypothesized that the prognostic genes affect tumor progression via tumor-mediated coagulation. MethodsWe detected the most significant prognostic genes of bladder cancer with The Cancer Genome Atlas dataset and validated them in 2 Gene Expression Omnibus datasets and 1 ArrayExpress dataset. Immunohistochemical tests were performed on a cohort of 80 individuals to further examine the prognostic genes. For the most reliable prognostic gene, its influence on coagulation was evaluated with gene knockdown followed by next-generation sequencing and cellular and animal experiments. ResultsDepletion of microtubule interacting and trafficking domain containing 1 (MITD1), a major prognostic gene of bladder cancer, significantly increased the tissue factor (TF) expression. MITD1 deficiency led to cytokinesis arrest, which, in turn, promoted the TF expression via unfolded protein response and c-Jun. The knockdown of IRE1, an essential kinase of unfolded protein response or the inactivation of c-Jun using c-Jun N-terminal kinase inhibitors weakened MITD1 deficiency– or dithiothreitol-induced TF upregulation. Cells lacking MITD1 promoted coagulation and metastasis in the experimental metastasis assay. ConclusionOur findings suggest the novel role of tumor prognostic genes upon the development of hypercoagulative phenotype and venous thromboembolism, thereby underlining the importance of anticoagulant therapy and shedding light on the therapeutic value of targeting MITD1 in bladder cancer.

Role of DNA methylation in cancer development and its clinical applications

Abstractmethyltransferase gene (DNA) methylation is a key process in epigenetic modification. This transformation leads to genomic instability that creates an impact on gene expression. DNA methylation is also involved in several mutations of tumour suppressor genes (TSGs) or proto‐oncogenes, resulting in cancer (hypermethylation and hypomethylation). Hypermethylation of promoter segments in TSGs causes transcriptional silencing, whereas hypomethylation of regulatory sequence activates proto‐oncogenes and retrotransposons. DNA methylation regulated by DNA methyltransferases is one of the essential epigenetic mechanisms that controls the cell cycle, cell proliferation, differentiation, apoptosis and transformation in eukaryotes, leading to genetic instability of tumour cells. Recent scientific research has highlighted that DNA methylation is a vital cancer biomarker source of several parts of body fluids that allow primary‐stage cancer cell detection during clinical screening. Nowadays, epigenetic biomarkers have been introduced as a decision maker with the potential to improve cancer prognosis. DNA methylation profiling helps to determine cancer at the deep genetic level, and create high impactful cancer screening approach in the future.

Possible poor prognosis in younger-onset Crohn's disease-associated anorectal cancer: A subanalysis of the Nationwide Japanese study.

Crohn's disease (CD)-associated intestinal cancers are characterized by their high incidence, particularly at the anorectal site in the Japanese population. Accumulating evidence revealed that younger-onset sporadic colorectal cancer may exhibit unique biological features. To the best of our knowledge, few previous articles reported clinicopathological features in patients with CD-associated anorectal cancer (CDAAC). Therefore, we aimed to clarify the relationship between the younger onset of cancer and clinicopathological characteristics and prognosis, and the efficacy of cancer surveillance in patients with CDAAC. CD patients who had been diagnosed with intestinal cancers from 1983 to 2020 were collected from 39 Japanese institutions in this study. Of 316 patients with CD-associated intestinal cancers, we analyzed 211 patients with CDAAC. We divided the patients into two groups according to the median age at cancer diagnosis (45 years old). Younger-onset CDAAC (YO-CDAAC) patients were significantly more likely to have a poor outcome than those with older-onset CDAAC (OO-CDAAC) in terms of both disease-free survival (DFS) (p = 0.0014) and overall survival (OS) (p = 0.023). Multivariate analysis showed that age under 45 years old at diagnosis of cancer was one of the independent factors for poor DFS and OS (hazard ratios: 2.15, 95% confidence interval: 1.09-4.26, p = 0.028, hazard ratios: 1.95, 95% confidence interval: 1.05-3.60, p = 0.033, respectively). Patients detected via surveillance showed significantly better DFS and OS rates than symptomatic patients in YO-CDAAC (p = 0.012 and 0.0031, respectively). YO-CDAAC may have a poorer prognosis compared with OO-CDAAC. Surveillance could be important to improve cancer prognosis, especially in young CD patients with anorectal disease.

Healthy lifestyle and cancer survival: A multinational cohort study.

Lifestyle factors after a cancer diagnosis could influence the survival of cancer 60 survivors. To examine the independent and joint associations of healthy lifestyle factors with mortality outcomes among cancer survivors, four prospective cohorts (National Health and Nutrition Examination Survey [NHANES], National Health Interview Survey [NHIS], UK Biobank [UKB] and Kailuan study) across three countries. A healthy lifestyle score (HLS) was defined based on five common lifestyle factors (smoking, alcohol drinking, diet, physical activity and body mass index) that related to cancer survival. We used Cox proportional hazards regression to estimate the hazard ratios (HRs) for the associations of individual lifestyle factors and HLS with all-cause and cancer mortality among cancer survivors. During the follow-up period of 37,095 cancer survivors, 8927 all-cause mortality events were accrued in four cohorts and 4449 cancer death events were documented in the UK and US cohorts. Never smoking (adjusted HR = 0.77, 95% CI: 0.69-0.86), light alcohol consumption (adjusted HR = 0.86, 95% CI: 0.82-0.90), adequate physical activity (adjusted HR = 0.90, 95% CI: 0.85-0.94), a healthy diet (adjusted HR = 0.69, 95% CI: 0.61-0.78) and optimal BMI (adjusted HR = 0.89, 95% CI: 0.85-0.93) were significantly associated with a lower risk of all-cause mortality. In the joint analyses of HLS, the HR of all-cause and cancer mortality for cancer survivors with a favorable HLS (4 and 5 healthy lifestyle factors) were 0.55 (95% CI 0.42-0.64) and 0.57 (95% CI 0.44-0.72), respectively. This multicohort study of cancer survivors from the United States, the United Kingdom and China found that greater adherence to a healthy lifestyle might be beneficial in improving cancer prognosis.

Association between Vitamin A and cancer: A review

Vitamin A is a fat-soluble micronutrient vital for the immune system, cellular differentiation, epithelial barrier function, and eyesight; they also play a significant function as a potent antioxidant regulating oxidative stress and the onset of cancer. There are two ways to get it through food: Provitamin A (beta-carotenoid) and preformed Vitamin A (retinol and retinyl ester). Uncontrolled cell proliferation and the development of metastatic features are characteristics of cancer initiated by agents such as aflatoxin, tobacco smoke’s carcinogenic compounds, and solar ultraviolet radiation. Vitamin A, an antioxidant vitamin, is hypothesized to exert chemo-preventive effects and reduce the risk of cancer by preventing tissue damage through the capture of organic free radicals, an end-product of numerous metabolic processes. This review is performed to investigate the association between Vitamin A and cancer. From March 2017 to March 2022, relevant articles were searched through PubMed, Science Direct, and Google Scholar databases. All the studies involving Vitamin A and cancer were included in this review. Intake of Vitamin A was significantly inversely associated with improved cancer prognosis. The present review demonstrates that there is an inverse association between Vitamin A and cancer treatment.

Deploying deep convolutional neural network to the battle against cancer: Towards flexible healthcare systems

The complexity of the facilities of healthcare providers goes beyond their physical articulation, function, and organization; it also involves integrating technology and healthcare activities that continuously evolve due to medical research and technological advancements. As a result, hospitals require a flexible approach that can accommodate the changing demands of patients, medical professionals, and researchers. This flexibility is essential in ensuring that hospitals can meet the diverse needs of their users and adapt to fast-changing medical requirements. Therefore, integrating analytical capabilities of Machine Learning algorithms in healthcare services is a vital aspect of Flexible Healthcare Systems. Furthermore, it enables hospitals to efficiently organize patient data and optimize treatment plans by analyzing vast amounts of patient data. In this paper, we explored the role of Machine Learning by applying Deep Convolutional Neural Networks on three unique datasets to predict the risk of developing cancer using health informatics and to demonstrate how computer-based vision can improve cancer prognosis by analyzing medical images. Furthermore, we have employed advanced CNNs for high-accuracy cancer detection in images, using a streamlined model that combines feature-detecting convolutional layers with complexity-reducing pooling layers which ensures effective cancer identification. The implementation of these models into healthcare delivery can potentially improve patient outcomes and system-level efficiencies, but carefully considering their limitations and ethical implications are essential.

Hierarchical graph representation learning with multi-granularity features for anti-cancer drug response prediction.

Patients with the same type of cancer often respond differently to identical drug treatments due to unique genomic traits. Accurately predicting a patient's response to drug is crucial in guiding treatment decisions, alleviating patient suffering, and improving cancer prognosis. Current computational methods utilize deep learning models trained on extensive drug screening data to predict anti-cancer drug responses based on features of cell lines and drugs. However, the interaction between cell lines and drugs is a complex biological process involving interactions across various levels, from internal cellular and drug structures to the external interactions among different molecules.To address this complexity, we propose a novel Hierarchical graph representation Learning with Multi-Granularity features (HLMG) algorithm for predicting anti-cancer drug responses. The HLMG algorithm combines features at two granularities: the overall gene expression and pathway substructures of cell lines, and the overall molecular fingerprints and substructures of drugs. Subsequently, it constructs a heterogeneous graph including cell lines, drugs, known cell line-drug responses, and the associations between similar cell lines and similar drugs. Through a graph convolutional network model, the HLMG learns the final cell line and drug representations by aggregating features of their multi-level neighbor in the heterogeneous graph. The multi-level neighbors consist of the node self, directly related drugs/cell lines, and indirectly related similar drugs/cell lines. Finally, a linear correlation coefficient decoder is employed to reconstruct the cell line-drug correlation matrix to predict anti-cancer drug responses. Our model was tested on the Genomics of Drug Sensitivity in Cancer (GDSC) and the Cancer Cell Line Encyclopedia (CCLE) databases. Results indicate that HLMG outperforms other state-of-the-art methods in accurately predicting anti-cancer drug responses.