Cancer Stage Research Articles

Application value of SOMATOM Force computed tomography in assisting the preoperative localization of colorectal cancer resection surgery

Background The objective of this study was to assess the application value of SOMATOM Force computed tomography (CT) in assisting the preoperative localization of colorectal cancer resection surgery. Method Retrospectively, the medical data of 120 inpatients with colorectal cancer were collected. The Kappa consistency test was used to evaluate diagnostic consistency in the localization and staging of colorectal cancer. The diagnostic value of preoperative SOMATOM Force CT detection was analyzed. Results In 120 colorectal cancer patients, the accuracy of SOMATOM Force CT for preoperative localization, T staging, and N staging of colorectal cancer were 91.7% (kappa = 0.837), 88.3% (kappa = 0.772) and 91.7% (kappa = 0.773), respectively. Among 45 rectum cancer patients, there were 19 positive cases with circumferential resection margin involvement, and the accuracy of SOMATOM Force CT detection was 86.7% (kappa = 0.767). The sensitivity, specificity, positive predictive value, and negative predictive value of SOMATOM Force CT detection in evaluating the circumferential resection margin involvement of rectum cancer were 78.95%, 96.15%, 93.75%, and 86.21%, respectively. Conclusions There was an important application value of SOMATOM Force CT in assisting the preoperative localization and tumor staging of colorectal cancer resection surgery. There was a good diagnostic value of preoperative SOMATOM Force CT detection in evaluating the circumferential resection margin involvement of rectum cancer.

Comparative Analysis of Vitamin D, Folic Acid, and Antioxidant Minerals in Various Stages of Lung Cancer

Comparative Analysis of Vitamin D, Folic Acid, and Antioxidant Minerals in Various Stages of Lung Cancer

Patient-Friendly Summary of the ACR Appropriateness Criteria®: Pretreatment Staging of Urothelial Cancer: 2024 Update

Patient-Friendly Summary of the ACR Appropriateness Criteria®: Pretreatment Staging of Urothelial Cancer: 2024 Update

Prognostic Value and Clinical Implication of Lymph Node-to-Primary Tumor SUV Ratio in Node-Positive Hypopharyngeal Squamous Cell Carcinoma Treated With Radiotherapy With or Without Chemotherapy.

The aim of this was to evaluate the prognostic significance of the nodal-to-primary tumor SUVmax ratio (NTR) in patients with node-positive hypopharyngeal squamous cell carcinoma (HPSCC) treated with radiotherapy with or without concurrent chemotherapy. The study aims to enhance prognostic accuracy by incorporating NTR into the American Joint Committee on Cancer (AJCC) staging system. This retrospective study included 191 patients with biopsy-proven node-positive HPSCC treated from 2005 to 2013. NTR was calculated as the ratio of SUVmax of metastatic lymph nodes to the primary tumor's SUVmax. Survival analyses were conducted using Cox regression models and Kaplan-Meier analysis. Receiver operating characteristic analysis compared the prognostic performance of the modified and AJCC staging systems. The median follow-up was 8.27 years, with 135 deaths (70.7%). High NTR (≥0.63) was significantly associated with worse overall survival (OS) and was an independent prognostic factor in multivariable analysis (adjusted hazards ratio [HR] = 1.63, P = 0.007). Median OS for high NTR was 17.4 months, compared with 75.2 months for low NTR. High NTR significantly predicted worse OS within AJCC stage IVA patients (HR = 6.09, P = 0.014). Patients in modified stage IVA (AJCC stage IVA with low NTR) had significantly longer OS than those in modified stage IVB (AJCC stage IVA with high NTR and AJCC stage IVB) (HR = 8.62, P = 0.003). The modified staging system incorporating NTR showed superior prognostic performance compared with the AJCC staging system. NTR is a significant independent prognostic factor for OS in node-positive HPSCC patients. Integrating NTR into the AJCC staging system improves prognostic accuracy.

Association of Cardiovascular Risk Factors and Coronary Calcium Burden with Epicardial Adipose Tissue Volume Obtained from PET-CT Imaging in Oncological Patients.

Whole-body positron emission tomography (PET)-computed tomography (CT) imaging performed for oncological purposes may provide additional parameters such as the coronary artery calcium (CAC) and epicardial adipose tissue (EAT) volume with cost-effective prognostic information in asymptomatic people beyond traditional cardiovascular risk factors. We evaluated the feasibility of measuring the CAC score and EAT volume in cancer patients without known coronary artery disease (CAD) referred to whole-body 18F-FDG PET-CT imaging, regardless of the main clinical problem. We also investigated the potential relationships between traditional cardiovascular risk factors and CAC with EAT volume. A total of 109 oncological patients without overt CAD underwent whole-body PET-CT imaging with 18F-fluorodeoxyglucose (FDG). Unenhanced CT images were retrospectively viewed for CAC and EAT measurements on a dedicated platform. Overall, the mean EAT volume was 99 ± 49 cm3. Patients with a CAC score ≥ 1 were older than those with a CAC = 0 (p < 0.001) and the prevalence of hypertension was higher in patients with detectable CAC as compared to those without (p < 0.005). The EAT volume was higher in patients with CAC than in those without (p < 0.001). For univariable age, body mass index (BMI), hypertension, and CAC were associated with increasing EAT values (all p < 0.005). However, the correlation between the CAC score and EAT volume was weak, and in multivariable analysis only age and BMI were independently associated with increased EAT (both p < 0.001), suggesting that potential prognostic information on CAC and EAT is not redundant. This study demonstrates the feasibility of a cost-effective assessment of CAC scores and EAT volumes in oncological patients undergoing whole-body 18F-FDG PET-CT imaging, enabling staging cancer disease and atherosclerotic burden by a single test already included in the diagnostic work program, with optimization of the radiation dose and without additional costs.

The importance of MRI in determining the stage of cervical cancer

Cervical cancer is one of the most common malignant tumours in women. The treatment of early and locally advanced stages of this cancer typically involves surgery, chemotherapy, and radiotherapy. However, there is no standardised therapy for metastatic cervical cancer due to the diverse manifestations of the disease. Therefore, timely diagnosis and staging of the carcinoma are crucial for maintaining the quality of life of patients. Imaging during the initial diagnostic evaluation is essential for accurately assessing the extent of the tumour and metastases, and for selecting the optimal therapy, with the FIGO system further emphasising this role. Compared to other imaging techniques, MRI provides detailed information on the location and size of the tumour, invasion into surrounding tissues, and the presence of distant metastases. This allows MRI to facilitate a tailored approach in therapy selection, taking into account the specific characteristics of the tumour. The integration of MRI into the diagnostic and therapeutic process improves clinical outcomes for patients with cervical cancer, enabling effective care. MRI is used alongside other imaging modalities in the diagnosis and treatment planning, and without it, precise staging of the disease and establishing a final diagnosis would not be possible.

Generalizable and automated classification of TNM stage from pathology reports with external validation

Cancer staging is an essential clinical attribute informing patient prognosis and clinical trial eligibility. However, it is not routinely recorded in structured electronic health records. Here, we present BB-TEN: Big Bird – TNM staging Extracted from Notes, a generalizable method for the automated classification of TNM stage directly from pathology report text. We train a BERT-based model using publicly available pathology reports across approximately 7000 patients and 23 cancer types. We explore the use of different model types, with differing input sizes, parameters, and model architectures. Our final model goes beyond term-extraction, inferring TNM stage from context when it is not included in the report text explicitly. As external validation, we test our model on almost 8000 pathology reports from Columbia University Medical Center, finding that our trained model achieved an AU-ROC of 0.815–0.942. This suggests that our model can be applied broadly to other institutions without additional institution-specific fine-tuning.

Standardized diagnosis of gastrointestinal tumors: an update regarding the situation in Germany.

To evaluate the current status of the diagnosis of gastrointestinal tumors in Germany by means of a survey of the oncological imaging working group of the German Radiological Society (DRG) with a focus on the CT protocols being used.Radiologists working in outpatient or inpatient care in Germany were invited. The survey was conducted between 10/2022 and 06/2023 using the SurveyMonkey web tool. Questions related to gastrointestinal cancer were asked with regard to the commonly used imaging modalities, body coverage, and contrast agent phases in CT as well as the use of oral or rectal contrast. The results of the survey were analyzed using descriptive statistics.Clear differences were identified regarding the acquired contrast phases in relation to the place of work - outpatient care, smaller hospitals, maximum care hospitals, or university hospitals. Variances were also recognized regarding oral and rectal contrast. Based on the results and international guidelines, proposals for CT protocols were derived.CT protocols in Germany show a heterogeneous picture regarding acquired contrast phases, as well as oral and rectal contrast for the staging of gastrointestinal cancer. Clear recommendations in the respective guidelines would aid in quality assurance and comparability between different centers. · The examination protocols for the staging of gastrointestinal tumors are heterogeneous in Germany.. · The application of oral and rectal contrast is handled differently at the various radiological centers.. · Standardization of imaging should be targeted.. · Gerwing M, Ristow I, Afat S et al. Standardized diagnosis of gastrointestinal tumors: an update regarding the situation in Germany. Fortschr Röntgenstr 2024; DOI 10.1055/a-2378-6451.

Effect of Fluorescence Lymph Node Mapping on Improving Diagnostic Values of CT D3 Lymph Node Staging for Right-Sided Colon Cancer

Background/Objectives: This study evaluated the impact of fluorescence lymph node mapping (FLNM) using indocyanine green (ICG) on the diagnostic accuracy of preoperative computed tomography (CT) in right-sided colon cancer. Methods: A total of 218 patients who underwent laparoscopic right hemicolectomy with D3 lymph node dissection (LND) were analyzed: 86 patients in the FLNM group and 132 in the conventional surgery group. The FLNM technique allowed for enhanced intraoperative visualization of lymph node (LN) and more precise dissection, improving the identification of metastatic LNs. The diagnostic value of preoperative CT staging was assessed in both the FLNM and control groups by calculating the apparent prevalence, true prevalence, sensitivity, specificity, positive predictive value (PPV), negative predictive value, positive likelihood ratio (PLR), negative likelihood ratio, false positive and false negative proportions, and accuracy. Results: FLNM increased the accuracy of CT staging for detecting D3 LN metastasis in advanced cancer cases, with a higher PPV, PLR, and accuracy. In the FLNM group, the false-positive rate was significantly reduced, and the specificity was higher compared to the control group. Multivariate analysis identified FLNM as an independent factor associated with improved D3 LN metastasis detection. These findings suggest that incorporating FLNM into surgical procedures enhances the diagnostic value of preoperative CT by improving the precision of LND, particularly in patients with advanced colon cancer. Conclusions: The use of FLNM for D3 LND enhances the diagnostic accuracy of cN staging in right-sided colon cancer by improving surgical precision.

Characteristics and Prognosis of Patients with Advanced Hepatocellular Carcinoma Treated with Atezolizumab/Bevacizumab Combination Therapy Who Achieved Complete Response.

To investigate the characteristics and prognosis of patients with advanced hepatocellular carcinoma (HCC) treated with atezolizumab and bevacizumab (Atz/Bev) who achieved a complete response (CR) according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST). A total of 120 patients with Eastern Cooperative Oncology Group performance status (PS) 0 or 1 and Child-Pugh A at the start of Atz/Bev treatment were included. Barcelona Clinic Liver Cancer stage C was recorded in 59 patients. The CR rate with Atz/Bev alone was 15.0%. The median time to CR was 3.4 months, and the median duration of CR was 15.6 months. A significant factor associated with achieving CR with Atz/Bev alone was an AFP ratio of 0.34 or less at 3 weeks. Adding transarterial chemoembolization (TACE) in the six patients who achieved a partial response increased the overall CR rate to 20%. Among the 24 patients who achieved CR, the median progression-free survival was 19.3 months, the median overall survival was not reached, and 14 patients (58.3%) were able to discontinue Atz/Bev and achieve a drug-free status. Twelve of these patients developed progressive disease (PD), but eleven successfully received post-PD treatments and responded well. Achieving CR by mRECIST using Atz/Bev alone or with additional TACE can be expected to offer an extremely favorable prognosis.

Interpretable Machine Learning-Aided Optical Deciphering of Serum Exosomes for Early Detection, Staging, and Subtyping of Lung Cancer.

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, underscoring an urgent need for strategies that enable early detection and phenotypic classification. Here, we conducted a label-free surface-enhanced Raman spectroscopic (SERS) analysis of serum exosomes from 643 participants to elucidate the biochemical deregulation associated with LC progression and the unique phenotypes of different LC subtypes. Iodide-modified silver nanofilms were prepared to rapidly acquire SERS spectra with a high signal-to-noise ratio using 0.5 μL of patient exosomes. We performed interpretable and automated machine learning (ML) analysis of differential SERS features of serum exosomes to build LC diagnostic models, which achieved accuracies of 100% and 81% for stage I lung adenocarcinoma and its preneoplasia, respectively. In addition, the ML-derived exosomal SERS models effectively recognized different LC subtypes and disease stages to guide precision treatment. Our findings demonstrate that spectral fingerprinting of circulating exosomes holds promise for decoding the clinical status of LC, thus aiding in improving the clinical management of patients.

Predictive Value of Multi-Phase CT Radiomics in Delineating Early and Advanced T Staging of Colon Cancer

This study leveraged the power of multi-phase CT radiomics, which extracts detailed features from multi-phase images, to explore the distinction between early (T1-T2) and advanced (T3-T4) colon cancer stages in each of multiple phases, providing valuable insights to healthcare professionals and enhancing their decision-making capabilities. A total of 191 patients with surgically confirmed primary colon cancer were retrospectively included, and multi-phase CT scans (non-enhanced contrast phase, arterial phase, portal venous phase, and delayed phase) were conducted within one week before surgery. Three-dimensional segmentation of colonic tumors was performed on the images of the four phases, and radiomics features of each colonic tumor were automatically extracted. Minimum redundancy maximum relevance (mRMR) was applied to features selection in each of the four phases. The least absolute shrinkage and selection operator logistic regression was conducted to determine the association between radiomics features and early (T1-T2) and advanced (T3-T4) stages of colon cancer. Additionally, diagnostic performance comparison was carried out in four phases. The mean (±SD) age of the 191 individuals was 61.87±13.137 years, with females comprising 43.5% of the cohort. The selected features for the non-enhanced, arterial, portal venous, and delayed phases numbered 7, 11, 6, and 10, respectively. In the test set, the AUC values for the on-enhanced, arterial, portal venous, and delayed phases were 0.86 (0.76-0.96), 0.84 (0.73-0.94), 0.82 (0.71-0.93), and 0.86 (0.75-0.97), with corresponding accuracies of 0.84, 0.80, 0.75, and 0.88, sensitivities of 0.73, 0.64, 0.86, and 0.68, and specificities of 0.91, 0.91, 0.68, and 1.00, respectively. DeLong's test revealed no statistically significant differences in the AUC values between the four phases within the test sets (P = 0.3233~ 0.9912). Multi-phase CT radiomics demonstrated substantial value in differentiating between early (T1-T2) and advanced (T3-T4) stages of patients with colon cancer.

EXPLORING MOLECULAR LINKS IN BRAIN TUMOUR BIOPSY TISSUES AND ALZHEIMER’S DISEASE

Abstract AIMS Generate and identify putative targets in the SORL1-network by mining online databases. Analyse 21 FFPE human brain tumour biopsy tissues through transcriptome sequencing performed by CeGaT (Tübingen, Germany) to explore differentially expressed genes. These biopsy samples are from consenting patients in association with Brain Tumour North West (BTNW) and the Royal Preston Hospital. METHOD Group comparisons are performed with the control and cancerous sample groups (low-grade glioma staying low, low-grade glioma becoming high and high-grade staying high). Further analysis involves comparing section and resection from the same patient for each cancer tissue group. Samples are explored on four different bioinformatic levels and sequenced on the Illumina platform. In Level 1 the data is demultiplexed and trimmed and in Level 2 trimmed reads are additionally mapped. Level 3 provides insights into the cell’s metabolic state and Level 4 performs several group comparisons. RESULTS Gain insights into differentially expressed genes’ presence in biopsy tissues from different stages of brain cancer, expression levels and links to clinical characteristics. Bioinformatic analysis provides data on quality control of the starting material, library preparation, sequencing parameters, and the Q30 value of the sequencing. CONCLUSION The analysis demonstrates molecular links in the SORL1-network in tissue from section and resection from a patient cohort to better understand disease recurrent and progression. Prospective bioinformatic work would explore interactions between significant targets identified to create a curated network that could predict druggable targets in gliomas.

CT Imaging as a Single Modality for Clinical Staging of Gastric Cancer in Limited Resource Centers: A Retrospective Pilot Study.

Gastric cancer disproportionately impacts populations in resource-limited settings. Within a safety-net network, we assessed the utility of computed tomography (CT) as a single staging modality. We utilized a clinical database of gastric cancer patients treated within the Los Angeles County safety-net hospital system from 2016 to 2023 in conjunction with retrospective imaging review by certified radiologists. We assessed agreement between clinical and pathological staging for patients who underwent curative gastrectomy using the Kappa coefficient. Of 107 patients with available CT imaging, 43.9% (n = 47) were staged with CT as a single modality. Most tumors displayed infiltrating (75%) or diffuse (28%) morphology, 41% displayed adequate gastric distention and regional lymphadenopathy was common (68%). Twenty-nine patients underwent curative gastrectomy. Overall agreement was minimal (κ = 0.29, 95% CI [0.071-0.51], p = 0.022), weak for T3/T4 tumors (κ = 0.50, 95% CI [0.17-0.82], p < 0.01), and weak for Hispanic/Latino patients (κ = 0.47, 95% CI [0.19-0.76], p < 0.01). There was minimal agreement between clinical and pathologic staging when assessing clinical stage by CT imaging alone, suggesting that CT is not adequate as a single modality staging tool. While every effort should be made to obtain multimodal staging, larger studies are warranted to improve CT imaging protocols for staging in resource-limited settings.

Adjuvant Therapy after Esophagectomy for Esophageal Cancer: Who Needs It?: Multi-institution Worldwide Observational Study

Objective: Based on current practice guidelines, we hypothesized that most patients with esophageal cancer, particularly those with locally advanced cancer, would benefit from adjuvant therapy after esophagectomy versus esophagectomy alone. We sought to obtain a granular estimate of patient-level risk-adjusted survival for each therapeutic option by cancer histopathology and stage. Background: Although esophagectomy alone is now an uncommon therapy for treating locally advanced esophageal cancer, the value of adjuvant therapy after esophagectomy is unknown. Methods: From 1970 to 2014, 22,123 consecutive patients from 33 centers on 6 continents (Worldwide Esophageal Cancer Collaboration) were diagnosed with biopsy-proven adenocarcinoma (n = 7526) or squamous cell carcinoma (n = 5625), of whom 10,873 received esophagectomy alone and 2278 additional adjuvant therapy. Random forests for survival and virtual-twin analyses were performed for all-cause mortality. Results: For adenocarcinoma, adjuvant therapy was beneficial only in pT4NanyM0 cancers (6–8 month survival benefit) and in pTanyN3M0 cancers (4–8 month benefit); a survival decrement was observed in pT1-3N0M0 cancers, with no effect on TanyN1-2M0 cancers. In squamous cell carcinoma, there was a 4 to 21 month survival benefit for pT3-4N0M0 cancers and a 4 to 15 month survival benefit for pT2-4N1-3M0 cancers. Conclusions: Adjuvant therapy after esophagectomy appears to benefit most patients with node-positive squamous cell carcinoma, but for adenocarcinoma, its value is limited to deep cancers and to those with substantial nodal burden. Future studies of the role of adjuvant therapies should treat these 2 cancers differently, with guidelines reflecting the histopathologic-appropriate survival value of adjuvant therapy.

Advanced Imaging for Localized Prostate Cancer

Background/Objectives: Prostate cancer is a prevalent malignancy often presenting without early symptoms. Advanced imaging technologies have revolutionized its diagnosis and management. This review discusses the principles, benefits, and clinical applications of multiparametric magnetic resonance imaging (mpMRI), micro-ultrasound (microUS), and prostate-specific membrane antigen positron emission tomography–computed tomography (PSMA PET/CT) in localized prostate cancer. Methods: We conducted a comprehensive literature review of recent studies and guidelines on mpMRI, microUS, and PSMA PET/CT in prostate cancer diagnosis, focusing on their applications in biopsy-naïve patients, those with previous negative biopsies, and patients under active surveillance. Results: MpMRI has demonstrated high sensitivity and negative predictive value in detecting clinically significant prostate cancer (csPCa). MicroUS, a newer technology, has shown promising results in early studies, with sensitivity and specificity comparable to mpMRI. PSMA PET/CT has emerged as a highly sensitive and specific imaging modality, particularly valuable for staging and detecting metastatic disease. All three technologies have been incorporated into urologic practice for prostate cancer diagnosis and management, with each offering unique advantages in different clinical scenarios. Conclusions: Advanced imaging techniques, including mpMRI, microUS, and PSMA PET/CT, have significantly improved the accuracy of prostate cancer diagnosis, staging, and management. These technologies enable more precise targeting of suspicious lesions during biopsy and therapy planning. However, further research, especially randomized controlled trials, is needed to fully establish the optimal use and inclusion of these imaging modalities in various stages of prostate cancer care.

Adaptive segmentation-to-survival learning for survival prediction from multi-modality medical images

Early survival prediction is vital for the clinical management of cancer patients, as tumors can be better controlled with personalized treatment planning. Traditional survival prediction methods are based on radiomics feature engineering and/or clinical indicators (e.g., cancer staging). Recently, survival prediction models with advances in deep learning techniques have achieved state-of-the-art performance in end-to-end survival prediction by exploiting deep features derived from medical images. However, existing models are heavily reliant on the prognostic information within primary tumors and cannot effectively leverage out-of-tumor prognostic information characterizing local tumor metastasis and adjacent tissue invasion. Also, existing models are sub-optimal in leveraging multi-modality medical images as they rely on empirically designed fusion strategies to integrate multi-modality information, where the fusion strategies are pre-defined based on domain-specific human prior knowledge and inherently limited in adaptability. Here, we present an Adaptive Multi-modality Segmentation-to-Survival model (AdaMSS) for survival prediction from multi-modality medical images. The AdaMSS can self-adapt its fusion strategy based on training data and also can adapt its focus regions to capture the prognostic information outside the primary tumors. Extensive experiments with two large cancer datasets (1380 patients from nine medical centers) show that our AdaMSS surmounts the state-of-the-art survival prediction performance (C-index: 0.804 and 0.757), demonstrating the potential to facilitate personalized treatment planning.

Breast cancer diagnosis and staging in Chile: A non-randomized survey-based study to assess frequency and delays.

Breast cancer progression involves physiological mechanisms such as metastasis. Delays in diagnosis and treatment increase the risk of mortality and are associated with barriers to healthcare access. In Chile, breast cancer is highly prevalent, and early diagnosis has improved, although disparities in the disease evolution persist. This study characterized diagnostic and staging tests, waiting times, and sociodemographic profiles to identify delays and inequities in care. Survey study. Using a non-probabilistic sample, a questionnaire was applied in an encrypted platform with prior informed consent. The instrument collected data on requested tests, associated times, staging, and sociodemographic characteristics. These variables were analyzed using descriptive statistics, tests of association, confidence intervals, and comparison tests using bootstrapping. A sample of 263 persons was obtained. The most requested tests were biopsy (99.62%) and blood tests (80.23%). The median number of tests requested was six (Q1:4, Q3:8), with a mean of 5.87 (standard deviation: 2.24). No significant differences were observed in the percentage of persons from whom the total number of examinations were requested according to the studied variables. The day-hour-result intervals ranged from 1 to 365 days. The median day-hour-result of the biopsy was 15 days (Q1:10, Q3:30). People between 40 and 49 years old, non-residents of the capital city, belonging to income quintile I, with high school education, from the public health system, with late-stage diagnosis had higher median day-hour-result in biopsy. There was no significant difference in the number of requested tests according to staging (I and II, or III and IV). Biopsy in Chile is the test of choice for diagnostic confirmation in breast cancer. Other tests are requested regardless of the diagnosis stage, contrary to the recommendations of clinical guidelines. Cancer prognosis is crucial, especially in countries with greater inequalities.

Risk score model for predicting mortality among patients with lung cancer

BackgroundTo develop an accurate mortality risk predictive model among patients with lung cancer.MethodsThe development cohort included 96,255 patients with lung cancer aged ≥19 years, who underwent a Korean National Health Insurance Service health check-up from 2005 to 2015. The validation cohort consisted of 18,432 patients (≥19 years) with lung cancer from another region. The outcome was all-cause mortality between January 1, 2005, and December 31, 2020.ResultsApproximately 60.5% of the development cohort died within a median follow-up period of 2.32 (0.72–5.00) years. Risk score was highest in participants aged ≥65 years, followed by those who underwent treatment, had a history of emergency room visits, and were current smokers. Participants treated by surgery had the lowest risk score, followed by combined surgery and chemotherapy, combined surgery and radiation therapy, women, and regular exercisers. The C statistic in the development and validation cohorts was 0.78 (95% confidence interval, 0.77–0.78) and 0.81 (95% confidence interval, 0.78–0.84), respectively.ConclusionAdvanced age, lung cancer stage, and treatment type were strong risk factors of mortality in lung cancer patients, while being a woman and exercise were preventive factors. These will aid in the prediction of mortality and management of lung cancer patients.

PER3 promoter hypermethylation correlates to the progression of pan-cancer

BackgroundMalignant cells exhibit reduced period circadian regulator 3 (PER3) expression. However, the underlying mechanisms of variations in PER3 expression in cancers and the specific function of PER3 in tumor progression remain poorly understood.ResultsWe explored multiple public databases, conducted bioinformatics analyses, and performed in vitro and in vivo experiments for validation. We found PER3 expression was decreased in most types of cancers, and PER3 downregulation was associated with a poor prognosis in 8 types of cancer. PER3 promoter methylation levels were increased in 11 types of cancer. Promoter hypermethylation (CpG islands [CGIs] cg12258811 and cg14204433) correlated with decreased PER3 expression in six cancers (breast invasive carcinoma, colon adenocarcinoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma [KIRP], lung adenocarcinoma [LUAD], and uterine corpus endometrial carcinoma). CGI cg12258811 hypermethylation was associated with reduced survival time and advanced cancer stages. Moreover, the bisulfite pyrosequencing assay confirmed CGI cg12258811 hypermethylation and its negative correlation with PER3 expression. In vitro and in vivo experiments demonstrated that PER3 inhibited KIRP and LUAD progression. Decitabine enhanced PER3 expression and inhibited KIRP cell functions by reducing promoter (cg12258811) methylation level.ConclusionsOur findings advanced the mechanistic understanding of variations in PER3 expression in cancers and confirmed the tumor-associated function of PER3 hypermethylation and downregulation.