Intervention For Cancer Survivors Research Articles

Machine learning applications in breast cancer survival and therapeutic outcome prediction based on multi-omic analysis.

The high heterogeneity within and between breast cancer patients complicates treatment determination and prognosis assessment. Treatment decision-making is influenced by various factors, such as tumor subtype, histological grade, and genotype, necessitating personalized treatment strategies. Prognostic outcomes vary significantly depending on patient-specific conditions. As a critical branch of artificial intelligence, machine learning efficiently handles large datasets and automates decision-making processes. The introduction of machine learning offers new solutions for breast cancer treatment selection and prognosis assessment. In the field of cancer therapy, traditional methods for predicting treatment and survival outcomes often rely on single or few biomarkers, limiting their ability to capture the complexity of biological processes comprehensively. Machine learning analyzes patients' multi-omic data and the intricate patterns of variations during cancer initiation and progression to predict patients' survival and treatment outcomes. Consequently, it facilitates the selection of appropriate therapeutic interventions to implement early intervention and improve treatment efficacy for patients. Here, we first introduce common machine learning methods, and then elaborate on the application of machine learning in the field of survival prediction and prognosis from two aspects: evaluating survival and predicting treatment outcomes for breast cancer patients. The aim is to provide breast cancer patients with precise treatment strategies to improve therapeutic outcomes and quality of life.

Liquid Biopsy in the Clinical Management of Cancers.

Liquid biopsy, a noninvasive diagnosis that examines circulating tumor components in body fluids, is increasingly used in cancer management. An overview of relevant literature emphasizes the current state of liquid biopsy applications in cancer care. Biomarkers in liquid biopsy, particularly circulating tumor DNA (ctDNA), circulating tumor RNAs (ctRNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), and other components, offer promising opportunities for early cancer diagnosis, treatment selection, monitoring, and disease assessment. The implementation of liquid biopsy in precision medicine has shown significant potential in various cancer types, including lung cancer, colorectal cancer, breast cancer, and prostate cancer. Advances in genomic and molecular technologies such as next-generation sequencing (NGS) and digital polymerase chain reaction (dPCR) have expanded the utility of liquid biopsy, enabling the detection of somatic variants and actionable genomic alterations in tumors. Liquid biopsy has also demonstrated utility in predicting treatment responses, monitoring minimal residual disease (MRD), and assessing tumor heterogeneity. Nevertheless, standardizing liquid biopsy techniques, interpreting results, and integrating them into the clinical routine remain as challenges. Despite these challenges, liquid biopsy has significant clinical implications in cancer management, offering a dynamic and noninvasive approach to understanding tumor biology and guiding personalized treatment strategies.

A regret theory-based even swaps method with complex linguistic information and its application in early-stage lung cancer treatment selection

Lung cancer is the cancer with the highest morbidity and mortality rate, and selecting treatment options for early-stage lung cancer patients is of great significance in improving cure rate. To help individuals make rational decisions, the even swap method, a multiple criteria decision-making (MCDM) model, provides an effective mechanism to make tradeoffs between criteria; however, the original even swap method ignored psychological characteristics of individuals and could not deal with complex linguistic information. To deal with the early-stage lung cancer treatment selection problem, this paper introduces generalized probabilistic linguistic term sets (GPLTSs) to describe complex linguistic information and proposes a generalized probabilistic linguistic even swap method based on the regret theory. Firstly, the upper and lower bounds corresponding to linguistic expressions are extracted to represent the uncertainty of GPLTSs. Then, a regret-rejoice function is introduced to express psychological characteristics of individuals when they making tradeoffs between criteria. Afterwards, a regret theory-based even swap method is proposed to rank alternatives. The proposed method is validated in the selection of early-stage lung cancer treatment options. Sensitivity analysis and comparative analysis are given to show the feasibility of the proposed method.

Intimacy and sexual functioning after cancer: The intersection with psychological flexibility

Cancer significantly impacts overall satisfaction with life (SWL). Psychological flexibility (PF) involves adapting to situational demands, balancing life demands, and committing to value-aligned behaviours, which can help survivors manage cancer-related distress. Given the lack of research examining how PF affects relationship and sexual satisfaction, our purpose was to elucidate the relationship between variables associated with partner intimacy, pillars of PF, and variables related to psychological wellness. We explored relationships between SWL and the pillars of PF (Valued Action, Behavioural Awareness, Openness to Experience) as mediating factors in the association between relationship and sexual satisfaction and SWL. Participants (113 male, 106 female) completed questionnaires measuring sexual function, intimacy, relationship and sexual satisfaction, PF, SWL, anxiety, and depression. Results indicated an equal percentage (57.5%) of males and females reported sexual dysfunction; however, varied patterns of relationships emerged between the sexes. There were significant relationships between SWL and relationship and sexual satisfaction. The mediation analyses showed that valued action and openness to experience partially mediated the relationship between relationship satisfaction and SWL. Interestingly, Valued Action was the only pillar of PF that emerged as a partial mediator between sexual satisfaction and SWL. Thus, value-aligned behaviours may be a key focus for intervention in cancer survivors.

Enhancing breast cancer treatment selection through 2TLIVq-ROFS-based multi-attribute group decision making.

Breast cancer is an extremely common and potentially fatal illness that impacts millions of women worldwide. Multiple criteria and inclinations must be taken into account when selecting the optimal treatment option for each patient. The selection of breast cancer treatments can be modeled as a multi-attribute group decision-making (MAGDM) problem, in which a group of experts evaluate and rank alternative treatments based on multiple attributes. MAGDM methods can aid in enhancing the quality and efficacy of breast cancer treatment selection decisions. For this purpose, we introduce the concept of a 2-tuple linguistic interval-valued q-rung orthopair fuzzy set (2TLIVq-ROFS), a new development in fuzzy set theory that incorporates the characteristics of interval-valued q-rung orthopair fuzzy set (IVq-ROFS) and 2-tuple linguistic terms. It can express the quantitative and qualitative aspects of uncertain information, as well as the decision-makers' level of satisfaction and dissatisfaction. Then, the 2TLIVq-ROF weighted average (2TLIVq-ROFWA) operator and the 2TLIVq-ROF weighted geometric (2TLIVq-ROFWJ) operator are introduced as two new aggregation operators. In addition, the multi-attribute border approximation area comparison (MABAC) method is extended to solve the MAGDM problem with 2TLIVq-ROF information. To demonstrate the efficacy and applicability of the suggested model, a case study of selecting the optimal breast cancer treatment is presented. The results of the computations show that the suggested MAGDM model is able to handle imprecision and subjectivity in complicated decision-making scenarios and opens new research scenarios for scholars.

Comprehensive genomic profiling and therapeutic implications for Taiwanese patients with treatment-naïve breast cancer.

Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression levels. The emergence of profiling technology has revealed multiple driver genomic alterations within each breast cancer subtype, serving as biomarkers to predict treatment outcomes. This study aimed to explore the genomic landscape of breast cancer in the Taiwanese population through comprehensive genomic profiling (CGP) and identify diagnostic and predictive biomarkers. Targeted next-generation sequencing-based CGP was performed on 116 archived Taiwanese breast cancer specimens, assessing genomic alterations (GAs), including single nucleotide variants, copy number variants, fusion genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status. Predictive variants for FDA-approved therapies were evaluated within each subtype. In the cohort, frequent mutations included PIK3CA (39.7%), TP53 (36.2%), KMT2C (9.5%), GATA3 (8.6%), and SF3B1 (6.9%). All subtypes had low TMB, with no MSI-H tumors. Among HR + HER2- patients, 42% (27/65) harbored activating PIK3CA mutations, implying potential sensitivity to PI3K inhibitors and resistance to endocrine therapies. HR + HER2- patients exhibited intrinsic hormonal resistance via FGFR1 gene gain/amplification (15%), exclusive of PI3K/AKT pathway alterations. Aberrations in the PI3K/AKT/mTOR and FGFR pathways were implicated in chemoresistance, with a 52.9% involvement in triple-negative breast cancer. In HER2+ tumors, 50% harbored GAs potentially conferring resistance to anti-HER2 therapies, including PIK3CA mutations (32%), MAP3K1 (2.9%), NF1 (2.9%), and copy number gain/amplification of FGFR1 (18%), FGFR3 (2.9%), EGFR (2.9%), and AKT2 (2.9%). This study presents CGP findings for treatment-naïve Taiwanese breast cancer, emphasizing its value in routine breast cancer management, disease classification, and treatment selection.

Comprehensive germline and somatic DDR genomic profiles of Chinese patients with multiple primary lung cancer.

e20019 Background: The number of multiple primary lung cancer (MPLC) patients has rapidly increased in recent years. Disruption of the DNA damage repair (DDR) gene is related to cancer risk, progression, and treatment selection. However, the characteristics and significance of DDR alterations remain undefined in MPLC. Methods: A total of 133 Chinese MPLC patients with 308 lesions were enrolled and 784 single-focus lung cancer (SFLC) patients were analyzed as a control in the present study. Genetic testing was performed by utilizing the next-generation sequencing (NGS) of 808 cancer-related genes including 276 DDR genes. The patients were divided into 3 groups: DDR-germline (germline variants, N = 11), DDR-somatic group (somatic variants, N = 98), and the non-DDR group (no DDR variants, N = 24). Results: The overall DDR variants were identified in 82.0% (109/133) of the patients, and a total of 283 variants were found, with almost all being somatic (254/283). The most commonly germline alterations were found in RAD50 (1.5%), WRN (1.5%) and BRCA2 (0.8%), while in the somatic mutations, TP53 (26.3%) showed the highest frequency. DDR-somatic group was more likely to have alterations in TP53, LRP1B, ERBB2 and MYC compared with DDR-germline group. Taken non-DDR group as reference, mutations in TP53 (P<0.05), ALK and PIK3CA were more common in DDR-germline group, but EGFR, RBM10, TP53, LRP1B, TERT and MYC (all P<0.05) in DDR-somatic group. Furthermore, the DDR-somatic group exhibits the highest median tumor mutational burden (6.56) compared with 3.55 (P<0.01) in DDR-germline and 3.69 (P<0.01) in non-DDR group. In addition, the copy number variation (CNV) was statistically different among the three groups (P<0.001). The proportion of copy number gain patients in DDR-somatic group is the highest (28.3%) compared with 12.0% in DDR-germline group and 10.9% in non-DDR group (P<0.01). DDR-somatic MPLC and SFLC patients possessed distinct somatic genomic characteristics, especially with significantly different prevalence in TP53, RBM10, KRAS, BRAF, and ALK (all P<0.05). Moreover, we also found notable differences in the prevalence of TP53 and CNV (both P<0.05) between DDR-germline MPLC and SFLC patients. Conclusions: MPLC patients exhibit a distinctive DDR mutations landscape. The differences in the mutation profile between the DDR-germline and DDR-somatic groups and the distinct actionable genes may indicate the different target-therapy choices for MPLC patients.

Characteristics of Orthodontic Treatment in Cancer Survivors: A Systematic Review.

Background: Survival rates of cancer patients have increased globally and across age groups. Challenges arising from craniofacial growth-development disturbances and dental abnormalities might warrant modifications to standard orthodontic pathways of care. Objective: The aim of this study was to systematically summarize and critically assess the available literature regarding the characteristics of orthodontic treatment in cancer survivors. Materials and Methods: A systematic search was conducted in seven databases for studies on malignant tumor survivors having undergone orthodontic intervention with fixed appliances following cancer treatment up to August 2023. The outcomes of interest included quantitative data regarding various characteristics of orthodontic treatment and the post-treatment period. The risk of bias was assessed individually with the Newcastle-Ottawa scale. Results: Out of 347 records, 4 cohort studies were eventually included in the qualitative synthesis. Leukemia was the most common malignancy type, with treatment involving mainly chemotherapy and/or radiotherapy. The duration of orthodontic treatment in cancer survivors varied. Occlusal results, quality of life, and satisfaction were comparable to healthy peers. However, in some survivors' groups, treatment was shorter and the final results were compromised. Root resorption and oral mucositis were reported among the treated cancer survivors. Reduced occlusal outcome stability during the retention period was also reported. Conclusions: Overall, the duration of orthodontic treatment varied among cancer survivors. The occlusal results achieved were similar to those of their healthy peers, though potentially less stable. Patient-reported outcomes did not differ significantly between cancer survivors and healthy individuals treated orthodontically.

Abstract PO1-17-05: Real-world effectiveness of palbociclib plus aromatase inhibitors (AI) in metastatic breast cancer patients with cardiovascular diseases

Abstract Background Breast cancer survivors are at risk for mortality from cardiovascular diseases (CVD). CVD and their treatments can impact breast cancer treatment selection and clinical outcomes. A cyclin dependent kinase 4/6 inhibitor (CDK4/6i) combined with endocrine therapy (ET) is more effective than ET alone for hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2) metastatic breast cancer (MBC). CDK4/6i plus ET is now the standard of care in the first-line setting for HR+/HER2 MBC. However, data on the effectiveness of CDK4/6i in MBC patients with CVD are limited. We compared overall survival (OS) and real-world progression-free survival (rwPFS) of palbociclib plus AI (PAL+AI) vs AI alone in HR+/HER2 MBC patients with CVD in routine US clinical practices. Methods The Flatiron Health longitudinal database contains electronic health records from >280 cancer clinics, representing >3 million actively treated cancer patients in the US. Using the Flatiron database, we conducted a retrospective analysis of 469 patients with HR+/HER2 MBC and CVD who started PAL+AI or AI as first-line therapy between February 2015 and March 2020. CVD prior to the initiation of PAL+AI or AI were identified based on their definitions within the National Cancer Institute-Comorbidity Index (NCI-CI), including myocardial infarction, congestive heart failure, peripheral vascular diseases, and cerebrovascular diseases. Patients were assessed from start of PAL+AI or AI to September 30, 2020 (data cutoff date), death, or last visit, whichever came first. OS was defined as months from start of PAL+AI or AI to death. rwPFS was defined as months from start of PAL+AI or AI to death or disease progression, evaluated based on clinical assessment or radiographic scan/tissue biopsy. Stabilized inverse probability treatment weighting (sIPTW) as primary analysis was used to balance baseline demographics and clinical characteristics. Cox proportional-hazards models were used to estimate the relative effectiveness of PAL+AI vs AI alone. Results Of the 469 eligible patients, 160 (34.1%) were treated with PAL+AI and 309 (65.9%) were treated with AI alone. Compared with AI-alone patients, those treated with PAL+AI were younger and were more likely to have de novo MBC, ≥2 metastatic sites, and lung/liver involvement. After sIPTW, patient characteristics were generally balanced. After sIPTW, median OS (95% confidence interval [CI]) was 40.7 months (30.956.0) in PAL+AI patients and 26.5 months (23.337.3) in AI patients (hazard ratio [HR]=0.732, 95% CI=0.5370.997, p=0.0476). Median rwPFS (95% CI) was 20.0 months (11.7–27.5) in PAL+AI patients and 12.5 months (9.718.3) in AI patients (HR=0.679, 95% CI=0.5120.900, p=0.0070). Consistent results were observed with multivariate Cox proportional-hazards models as sensitivity analysis. See Table for baseline patient characteristics and outcome results. Conclusions First-line PAL in combination with AI is associated with prolonged OS and rwPFS in patients with HR+/HER2 MBC and CVD in a real-world setting compared with AI alone. Further studies with larger cohorts and comprehensive assessments of comorbidities are needed to provide additional evidence of outcomes and safety of CDK4/6i plus AI for MBC patients with various comorbid conditions in routine clinical practice. Citation Format: Adam Brufsky, Xianchen Liu, Benjamin Li, Lynn McRoy, Connie Chen, Doris Makari, Rachel Layman, Hope Rugo. Real-world effectiveness of palbociclib plus aromatase inhibitors (AI) in metastatic breast cancer patients with cardiovascular diseases [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-17-05.

Digital Pathology for Better Clinical Practice.

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis

PurposeResearch on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin’s lymphoma, breast, uterine, cervical, and colorectal cancer).MethodsThis study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used.ResultsSubjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin’s lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types.ConclusionIdentifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

Adaptation and study protocol for harvest for health together Arizona: A mentored community garden intervention for survivors of cancer

BackgroundCurrent health behavior recommendations for skin cancer prevention, treatment, and survivorship are the same for survivors of other cancers; they include eating a healthy diet, being physically active, maintaining a healthy weight, and minimizing ultraviolet (U.V.) exposure. Few interventions exist to support health behaviors beyond U.V. exposure. We adapted Harvest for Health, a home-based mentored gardening intervention for cancer survivors, for implementation in Arizona as a community-based intervention. MethodsStakeholder-informed adaptations for Harvest for Health Together Arizona (H4H2-AZ) included updating intervention materials to be relevant to the arid desert environment, emphasizing the importance of sun safety in cancer survivorship, and shifting from a home-based to a community-based delivery model. Participants will be enrolled in cohorts aligned with growing seasons (e.g., spring, monsoon, fall) and matched to an individual 30 ft2 community garden plot for two growing seasons (6 months). Original intervention components retained are: 1) Master Gardeners deliver the intervention providing one-to-one mentorship and 2) gardening materials and supplies provided. This pilot six-month single-arm intervention will determine feasibility, acceptability, and appropriateness of an evidence-based adapted mentored community gardening intervention for survivors of skin cancer as primary outcomes. Secondary outcomes are to explore the effects on cancer preventive health behaviors and health-related quality of life. DiscussionThis pilot single-arm intervention will determine feasibility, acceptability, and appropriateness of an evidence-based adapted mentored community gardening intervention for survivors of skin cancer. If successful, the intervention could be widely implemented throughout existing Master Gardener programs and community garden networks for survivors of other cancers. Trial registrationClinicalTrials.gov identifier: NCT05648604. Trial registered on December 13, 2022.

Abstract 5015: Genomic profiling of colorectal cancer - insights from liquid biopsy comparisons between U.S. and China cohorts

Abstract Background: Molecular characteristics play a pivotal role in cancer diagnosis, treatment selection, and disease monitoring across various tumor types. While previous research has elucidated the molecular classification of colorectal cancer using tissue NGS, limited investigation has explored the molecular profile of colorectal cancer through liquid biopsy, especially across diverse human races. This study presents a comprehensive genomic profiling analysis of colorectal cancer patients, using a globally harmonized liquid biopsy assay to compare patient cohorts from both the U.S. and China. Methods: The prospective study is part of Predicine’s Phoenix Program, a global molecular biomarker screening initiative across multiple solid tumors. At present, the study has enrolled 57 patients in the U.S. and 62 patients in China, all presenting with advanced colorectal cancer. A 10ml blood sample was collected from each patient and tested using PredicineCARE, an NGS-based liquid biopsy assay, to profile somatic mutations, copy number variations, and gene fusions among these patients. Results: The assay, validated in both the U.S. and China using the same reference materials, achieved a LOD of 0.25% mutation allele frequency, with a positive predictive value exceeding 99%. Subsequently, the assay was applied to profile molecular aberrations in colorectal patients in both the U.S. and China. Among U.S. patients, the most commonly altered genes were APC (60%), KRAS (56%), TP53 (54%), MYC (25%), PIK3CA (16%), and EGFR (14%). In Chinese patients, the predominant altered genes were TP53 (48%), APC (42%), KRAS (32%), GNAS (21%), EGFR (16%), and PIK3CA (11%). The prevalence of GNAS variations was significantly higher in China than in the U.S. (p < 0.05), while the prevalence of APC (p < 0.05), KRAS (p < 0.01), and MYC (p < 0.001) variations was significantly higher in the U.S. than in China. Conclusions: This study reveals the extensive mutational landscape in advanced colorectal cancer patients through liquid biopsy. Distinct prevalence patterns in certain genes between the U.S. and China cohorts offer novel biomarkers for clinical diagnosis and provide insights for targeted therapy mechanism studies. Citation Format: Haoran Tang, Cancan Jia, Feng Xie, Yue Zhang, Xiaoxi Dong, Yong Huang, Shidong Jia. Genomic profiling of colorectal cancer - insights from liquid biopsy comparisons between U.S. and China cohorts [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 5015.

Abstract 7566: Identification of cancer subtypes with a ctDNA-based targeted methylation assay

Abstract Introduction: Identifying cancer subtypes is necessary for cancer diagnosis, prognosis determination, and treatment selection. Furthermore, as transformation between subtypes is increasingly recognized as a key resistance mechanism to targeted therapies, serial subtype reassessment is likely to gain adoption. Cancer subtypes have traditionally been determined by pathologists based on histology; more recently, molecular subtyping has been performed using IHC, RNAseq, or assays that detect genetic alterations. However, these methods have significant limitations, including tissue biopsy requirement (IHC and RNAseq), low discriminative resolution for distinct transcriptional programs (IHC and mutation detection), and poor reproducibility and feasibility (RNAseq). The GRAIL plasma-only, ctDNA-based targeted methylation platform is a robust, biopsy-free, scalable assay that can distinguish cancer methylation patterns between different cancer signal origins through the use of a proprietary classifier. Here, we explore the GRAIL platform’s potential to detect finer-scale differences in cancer biology by developing classification algorithms for subtyping of three common cancer types. Methods: As part of the Circulating Cell-free Genome Atlas (NCT02889978) and STRIVE (NCT03085888) studies, clinical data were recorded and plasma samples were collected, accessioned, stored, and processed through GRAIL’s targeted methylation assay from 3,989 cancer and 6,013 non-cancer participants. We developed algorithms to predict cancer status and subtype for breast (triple negative breast cancer [TNBC] model; 531 cancer training participants), lung (lung histology model; 334 cancer training participants), and head and neck (HPV model; 3090 cancer training participants) cancers. Dimensionality reduction of methylation data was performed to illustrate subtype separation within these cancer types. Performance of these three algorithms was assessed on a held-out cohort of cancer samples (184 breast, 241 lung, 67 head and neck) with detectable ctDNA. Results: The lung histology model correctly classified 95% (105/111) of adenocarcinomas, 88% (68/77) of squamous cell carcinomas, and 94% (59/63) of lung neuroendocrine carcinomas and tumors. The TNBC model correctly classified 84% (58/69) of TNBCs and 82% (94/115) of non-TNBCs. The HPV model correctly identified 98% (48/49) of HPV-positive head and neck cancers, and 89% (16/18) of HPV-negative head and neck cancers. Conclusions: GRAIL’s proprietary ctDNA-based targeted methylation platform demonstrates the ability to accurately predict cancer subtypes in multiple cancers using only a plasma sample without the need for tumor biopsy. Future efforts will be directed towards generalizing the GRAIL subtyping method to additional cohorts and cancer types. Citation Format: Tracy Nance, Timothy Shaver, Yifan Zhou, Margaret Antonio, Yinjie Gao, Jonathan Heiss, Robert Calef, Joseph Hiatt, Oliver Venn, Joerg Bredno, John Beausang, Lisa Newman, Charles Swanton, Chun Zhang. Identification of cancer subtypes with a ctDNA-based targeted methylation assay [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 7566.

Accelerated Aging in Cancer Survivors: Cellular Senescence, Frailty, and Possible Opportunities for Interventions.

The population of cancer survivors has markedly increased due to the rapid improvements in cancer treatment. However, cancer survivors experience accelerated aging, which leads to chronic diseases and other age-related conditions, such as frailty. Those conditions may persist years after cancer diagnosis and treatment. Cellular senescence, a hallmark of aging, is one of the mechanisms that contribute to accelerated aging in cancer survivors. Several aging measures, including measures based on clinical markers and biomarkers, have been proposed to estimate the aging process, and some of them have shown associations with mortality and frailty in cancer survivors. Several anti-aging interventions, including lifestyle changes and anti-aging drugs, have been proposed. Future research, particularly in large-scale studies, is needed to determine the efficiency of these aging measures and anti-aging interventions before considering their application in clinics. This review focuses on the mechanisms of cellular senescence and accelerated aging in cancer survivors, assessment of the aging process using clinical markers and biomarkers, and the high prevalence of frailty in that population, as well as possible opportunities for anti-aging interventions. A deeper understanding of aging measures and anti-aging interventions in cancer survivors will contribute to the development of effective strategies to mitigate accelerated aging in cancer survivors and improve their quality of life.

Medication-based Comorbidity Measures and Prostate Cancer Treatment Selection

IntroductionWe aimed to assess the association between comorbidities and prostate cancer management. Patients and methodsWe studied 12,603 South Australian men diagnosed with prostate cancer between 2003 and 2019. Comorbidity was measured one year prior to prostate cancer diagnosis using a medication-based comorbidity index (Rx-Risk). Binomial logistic regression analyses were used to assess the association between comorbidities and primary treatment selection (active surveillance, radical prostatectomy (RP), external beam radiotherapy (EBRT) with or without androgen deprivation therapy (ADT), brachytherapy, ADT alone, and watchful waiting (WW)). Certain common comorbidities within Rx-Risk (cardiac disorders, diabetes, chronic airway diseases, depression and anxiety, thrombosis, and chronic pain) were also assessed. All models were adjusted for sociodemographic and tumor characteristics. ResultsLikelihood of receiving RP was lower among men with Rx-Risk score ≥3 (odds ratio (OR) 0.62, 95%CI:0.56-0.69) and Rx-Risk 2 (OR 0.80, 95%CI:0.70-0.92) compared with no comorbidity (Rx-Risk ≤0). Men with high comorbidity (Rx-Risk ≥3) were more likely to have received ADT alone (OR 1.76, 95%CI:1.40-2.21), EBRT (OR 1.30, 95%CI:1.17-1.45) or WW (OR 1.49, 95%CI:1.19-1.88) compared with Rx-Risk ≤0. Pre-existing cardiac and respiratory disorders, thrombosis, diabetes, depression and anxiety, and chronic pain were associated with lower likelihood of selecting RP and higher likelihood of EBRT (except chronic airway disease) or WW (except diabetes and depression and anxiety). Cardiac disorders and thrombosis were associated with higher likelihood of selecting ADT alone. Furthermore, age had greater effect on treatment choice than the level of comorbidity. ConclusionHigh comorbidity burden was associated with primary treatment choice, with significantly less RP and more EBRT, WW and ADT alone among men with higher levels of comorbidity. Each of the individual comorbid conditions also influenced treatment selection.

A multisite initiative to increase medical oncologists’ utilization of clinical pathways in the selection of systemic cancer treatment.

575 Background: The Swedish Cancer Institute (SCI) recognizes that quality cancer care is a systemwide commitment. In 2020, SCI implemented ClinicalPath (formerly Via Oncology). The ClinicalPath tool assists in the selection of systemic treatment protocols. The protocols balance considerations of clinical efficacy, safety, toxicities, and cost. National utilization rate for ClinicalPath ranges between 50-70%. In 2021, ClinicalPath monthly utilization by SCI medical oncologists was 56%. This initiative aimed to increase utilization of ClinicalPath by SCI Medical Oncologists, across the three main campuses, to above 70% by the end of 2022. Methods: The Plan Do Study Act framework was used. Utilization was defined as accessing the ClinicalPath tool. Utilization data was abstracted from an Epic Workbench Report that was filtered to reflect practicing SCI medical oncologists and the 25 diagnoses included in ClinicalPath. An introduction email and meeting request was sent to eight Medical Directors. A fishbone diagram was used to identify the potential causes of low utilization. PDSA 1 interventions included 1:1 meeting with each Medical Director to validate baseline data for cascading to their oncologists and encourage engagement. PDSA 2 included monthly “Quality Messages” with oncologists’ monthly utilization rate. In addition, a public recognition of “Most Improved Utilization” from Q1 to Q2 was done by the SCI Executive Medical Director. PDSA 3 focused on wide dissemination of the initiative through presentations that included a link to a “Tips & Tricks for ClinicalPath” video at SCI executive and department meetings. Public recognition of “Top Performers” from Q3 was published in the SCI newsletter. Results: The process measure of 1:1 meeting with Medical Directors was achieved at 100%. During PDSA 1 the outcome measure of monthly utilization rates improved to 71%. The 2nd PDSA cycle yielded a utilization rate of 84%. The 3rd PDSA cycle monthly utilization rate by the end of 2022 was 86%. At the most recent tracking into 2023, the utilization rate showed sustainability with achieved rates of 83%, 80%, 80% for Jan, Feb, March. Conclusions: Engaging the SCI Medical Directors and sharing individual performance data with the medical oncologists was a simple intervention yet yielded a significant improvement in their ClinicalPath utilization rates. Public recognition, along with addressing common barriers through education resulted in further improvement. This approach serves as a model for increasing utilization of a point of care clinical decision tool.

The prevalence and risk factors for physical impairments in Chinese post-cancer treated breast cancer survivors: a 4 years’ cross-sectional study at a single center

The incidence of breast cancer in China was 19.2% in 2018, with a five-year survival rate of up to 80%. The impairments that may result from breast cancer treatment, such as lymphedema, pain, and symptoms related to nerve damage, could have long-term side effects. Its prevalence and symptom profile have been commonly reported in various countries, but such data are rarely available for China. Physical function was assessed in 138 breast cancer survivors (BCSs) in the study. The prevalence of lymphedema (65.9%) was higher than that of pain (31.2%), shoulder range of motion (ROM) restriction (20.3%), grip strength restriction (GSR) (21.7%) and paresthesia (11.6%). These impairments mainly appeared within 28 months after breast cancer diagnosis, but could happen in 10 years. Carcinoma in situ and radiotherapy (RT) were related to the occurrence of lymphedema (respectively B = -1.8, p = 0.003; B = 1.3, p = 0.001). RT and delayed rehabilitation time (DRT) may increase the severity of lymphedema (respectively p = 0.003, p = 0.010). Breast conserving surgery (B = -2.1, p = 0.002) and the occurrence of AWS (B = 3.1, p = 0.006) were related to the occurrence of pain. The occurrence of brachial plexus injury (BPI) (B = 3.1, p < 0.001) and pain (B = 1.9, p = 0.002) improved the occurrence of shoulder ROM restriction. The occurrence of BPI (B = 3.6, p < 0.001) improved the occurrence of GSR. The occurrence of pain (B = 2.1, p = 0.001) improved the occurrence of paresthesia. These findings prompt us to further investigate the actual rehabilitation needs of survivors and the specific barriers to rehabilitation in the following research.

Incidence of Major Depression, Suicidal Ideation, and Mental Health Treatment Amongst Cancer Survivors

Receiving a cancer diagnosis and undergoing subsequent treatments can result in a significant psychological burden for cancer patients. However, there is conflicting literature on the incidence of major depression in cancer patients compared to patients without cancer. The purpose of this study was to investigate and further clarify the incidence of major depression, associated treatments, and suicidal ideation in cancer survivors compared to a non-cancer cohort. This is a retrospective, population-based study using survey responses from the National Survey on Drug Use and Health collected from January 2015 to December 2019. Survey data sets were queried for all respondents aged 18 years or older who provided a cancer history. Patients with a reported history of cancer ("cancer survivors") were further stratified by whether they reported a "recent" cancer diagnosis within the past 12 months. Survey responses were then evaluated for recent diagnoses of and treatments for major depressive disorder and suicidal ideation. Rates were compared between cancer survivors and participants without cancer using the Pearson χ2 test and multivariable logistic regression models, respectively. Among the 212,411 survey respondents identified, 7,635 (3.6%) reported a cancer history, with 1,486 (0.7%) reporting a recent cancer history. The incidence of major depression was not different between cancer survivors and participants without cancer (9.3% vs. 9.2%; p = 0.762), though the incidence was slightly higher amongst recent cancer survivors (10.0% vs. 9.2%; p = 0.259). Among patients diagnosed with major depression, cancer survivors were significantly more likely to receive treatment for depression (78.6% vs. 60.3%, p<0.001), with 72.6% discussing depressive symptoms with a medical professional and 64.3% receiving prescription medication. Suicidal ideation was significantly lower among cancer survivors (5.1% vs. 6.2%, p<0.001) including recent survivors (5.0% vs. 6.2%, p<0.001). Suicidal ideation was higher in patients with underlying major depression in both cancer survivors and participants without cancer (30.6% vs. 35.6%, p = 0.015). On logistic regression, respondents with underlying depression receiving treatment were more likely to have suicidal ideation (OR: 1.49; p<0.001) while having a cancer diagnosis did not correlate with suicidal ideation (OR: 0.87; p = 0.869). There was no significant overall difference in the incidences of major depression between cancer survivors and patients without cancer. However, one consideration is the under-diagnosis depression among cancer survivors. Symptoms of depression may be overlooked and mistakenly attributed to appropriate grief from a cancer diagnosis. Among patients diagnosed with major depression, cancer survivors were more likely to receive treatment for depression. These results highlight the importance of early depression assessment and treatment for cancer survivors.

Value of biplane transrectal ultrasonography plus micro-flow imaging in preoperative T staging and rectal cancer diagnosis in combination with CEA/CA199 and MRI

BackgroundRectal cancer is one of the most common malignant tumors and has a high incidence rate and fatality rate. Accurate preoperative T staging of rectal cancer is critical for the selection of appropriate rectal cancer treatment. Various pre-operative imaging methods are available, and the identification of the most accurate method for clinical use is essential for patient care. We investigated the value of biplane transrectal ultrasonography (TRUS) combined with MFI in preoperative staging of rectal cancer and explored the value of combining TRUS plus MFI with CEA/CA199 and MRI.MethodsA total of 87 patients from Daping Hospital with rectal cancer who underwent TRUS examination plus MFI were included. Grades of MFI were determined by Alder classification. Among the total patients, 64 underwent MRI and serum CEA/CA199 tests additionally within one week of TRUS. Pathological results were used as the gold standard for cancer staging. Concordance rates between TRUS, MRI, and CEA/CA199 for tumors at different stages were compared.ResultsThere were no significant differences between the Alder classification and pathological T staging. The concordance rate of TRUS and MFI for rectal cancer T staging was 72.4% (K = 0.615, p < 0.001). Serum CEA and CA199 levels were significantly different in tumors at different stages and increased progressively by pathological stage (p < 0.001); the accuracy rate was 71.88% (K = 0.599, p < 0.001), while that of MRI was 51.56% (K = 0.303, p < 0.001), indicating that TRUS had higher consistency in the preoperative T staging of rectal cancer. The combination of TRUS, MRI, and CEA/CA199 yielded an accuracy rate of 90.6%, which was higher than that of any method alone.ConclusionsPreoperative T staging of rectal cancer from biplane TRUS plus MFI was highly consistent with postoperative pathological T staging. TRUS combined with MRI and serum CEA/CA199 had a greater value in the diagnosis of rectal cancer and a higher diagnostic rate than any examination alone.