Tumor Lymph Node Metastasis Research Articles

Comparison of multiple machine learning models for predicting prognosis of pancreatic ductal adenocarcinoma based on contrast-enhanced CT radiomics and clinical features

ObjectiveThe aim of this study was to evaluate the prognostic potential of combining clinical features and radiomics with multiple machine learning (ML) algorithms in pancreatic ductal adenocarcinoma (PDAC).MethodsA total of 116 patients with PDAC who met the eligibility criteria were randomly assigned to a training or validation cohort. Seven ML algorithms, including Supervised Principal Components, stepwise Cox, Random Survival Forest, CoxBoost, Least absolute shrinkage and selection operation (Lasso), Ridge, and Elastic network, were integrated into 43 algorithm combinations. Forty-three radiomics models were constructed separately using radiomics features extracted from arterial phase (AP), venous phase (VP), and combined arterial and venous phase (AP+VP) images. The concordance index (C-index) of each model was calculated. The model with the highest mean C-index was identified as the best model for calculating the radiomics score (Radscore). Univariate and multivariate Cox analyses were used to identify independent prognostic indicators and create a clinical model for prognosis prediction. The multivariable Cox regression was used to combine Radscore with clinical features to create a combined model. The efficacy of the model was evaluated using the C-index, calibration curves, and decision curve analysis (DCA).ResultsThe model based on the Lasso+StepCox[both] algorithm constructed using AP+VP radiomics features showed the best predictive ability among the 114 radiomics models. The C-indices of the model in the training and validation cohorts were 0.742 and 0.722, respectively. Based on the results of the univariate and multivariate Cox regression analyses, sex, Tumor-Node-Metastasis (TNM) stage, and systemic inflammation response index were included to build the clinical model. The combined model, incorporating three clinical factors and AP+VP-Radscore, achieved the highest C-indices of 0.764 and 0.746 in the training and validation cohorts, respectively. In terms of preoperative prognosis prediction for PDAC, the calibration curve and DCA showed that the combined model had a good consistency and greatest net benefit.ConclusionA combined model of clinical features and AP+VP-Radscore screened using multiple ML algorithms has an excellent ability to predict the prognosis of PDAC and may provide a noninvasive and effective method for clinical decision-making.

Hsa_circRNA_000166 accelerates breast cancer progression via the regulation of the miR-326/ELK1 and miR-330-5p/ELK1 axes

Purposes To probe the expression, clinical significance, roles, and molecular mechanisms of circRNA_000166 in breast cancer (BC). Methods Clinical tissue samples were gathered from 84 BC patients who underwent surgery at the Affiliated Hospital of Chengde Medical College. Clinical data were obtained from medical records and postoperative follow-up. Expression levels of circRNA_000166, miR-326, miR-330-5p, and ELK1 mRNA in BC tissues and cells were measured by qRT-PCR, and ELK1 protein levels were assessed by WB. Pearson’s correlation analysis evaluated the interrelationships between these RNAs in clinical samples. Luciferase reporter assays verified the interactions between miR-326/miR-330-5p and circRNA_000166, as well as between miR-326/miR-330-5p and ELK1. Cell proliferation, migration, and apoptosis were examined using CCK-8, colony formation, transwell, and flow cytometry assays, respectively. Results CircRNA_000166 was highly expressed in BC tissues and inversely correlated with miR-326/miR-330-5p levels but positively with ELK1 mRNA levels. ELK1 mRNA also inversely associated with miR-326/miR-330-5p levels in BC tissues. Importantly, our findings demonstrated that circRNA_000166 targets miR-326 and miR-330-5p, while ELK1 is the target of miR-326 and miR-330-5p in BC cells. CircRNA_000166 levels positively correlated with tumour size, TNM stage, histological grade, and lymph node metastasis, and negatively associated with postoperative progression-free survival (PFS) and overall survival (OS) in BC patients. CircRNA_000166 was also highly expressed in BC cells, and knockdown of circRNA_000166 reduced proliferation and migration, and increased apoptosis via miR-326/ELK1 and miR-330-5p/ELK1 pathways in vitro. Conclusion CircRNA_000166 enhances BC progression through miR-326/ELK1 and miR-330-5p/ELK1 pathways and shows potential as a biomarker for BC diagnosis and treatment.

Exploration of the pattern of lymph node metastasis in esophageal cancer based on membrane anatomy theory

AbstractObjectiveTo analyze the pattern of lymph node metastasis in esophageal cancer based on the theory of membrane anatomy.MethodsA retrospective analysis was conducted on 143 patients who underwent esophageal surgery at the Cancer Hospital of the Chinese Academy of Medical Sciences from March 2021 to March 2022. Lymph node metastasis was observed and categorized according to postoperative T staging. The characteristics and patterns of lymph node metastasis in different regions were observed, and the lymph node metastasis patterns in patients with clinical T3 esophageal cancer were analyzed using membrane anatomy theory.ResultsAmong the 143 patients with esophageal squamous cell carcinoma, 21 were treated with surgery alone, while the rest received preoperative adjuvant therapy. A total of 5456 lymph nodes were cleared from the 143 patients, with 204 positive lymph nodes, resulting in a positive rate of 3.74%. In the thoracic lymph node dissection, the metastatic rates exceeded 5% for the following regions: 106recR (17.36%), 106recL (12.5%), 107 (10.42%), and 108 (5.56%) station. When analyzing the abdominal lymph node metastasis, the metastatic rates exceeded 5% for regions 7 (13.19%), 3a (7.64%), 2 (6.94%), and 1 (6.25%) station. Group analysis of patients with esophageal squamous cell carcinoma before postoperative pathological T3 stage revealed an increasing trend in tumor lymph node metastasis rate with later T staging. Lymph node metastasis in region 106recR can occur early, with a metastasis rate of 18.37% in T1 tumors. Analysis of lymph node metastasis characteristics in 103 patients clinically staged as T3 showed that 3966 lymph nodes were cleared, with 186 positive nodes, resulting in a positive rate of 4.69%. Lymph node metastasis rates were higher in regions 106recL, 106recR, 107, 108, 110, 1, 2, 3a, and 7, all exceeding 5%.ConclusionThe theory of membrane anatomy can effectively explain the pattern of lymph node metastasis in esophageal cancer.

Global Leadership Initiative on Malnutrition criteria: Clinical benefits for patients with gastric cancer.

Malnutrition is a prevalent condition among patients with gastric cancer and is associated with poor survival outcomes. This study aimed to evaluate the clinical utility of the Global Leadership Initiative on Malnutrition (GLIM) criteria in predicting survival among patients with gastric cancer. The multicenter retrospective cohort study (INSCOC study) included 1406 patients enrolled between December 2012 and April 2020, with follow-up data collected until June 2023. Various indices for muscle evaluation, such as calf circumference (CC) and body weight-standardized hand grip strength (HGS/W), were used to diagnose malnutrition. Kaplan-Meier curves were used to analyze the relationship between nutrition status, as defined by GLIM criteria, and survival outcomes in these patients. The analysis revealed that using CC or HGS/W as positive indicators of malnutrition effectively identified patients with survival-related malnutrition. The incidence of malnutrition was 54.5%, with patients' median overall survival times of 1169 days for stage I and 575 days for stage II cancer (P < 0.001). Malnutrition was identified as an independent risk factor for survival. Additionally, a nomogram developed through Cox regression analysis demonstrated precise predictive capability, incorporating factors such as tumor node metastasis staging, Karnofsky Performance Status Scale, direct bilirubin levels, and nutrition intervention. The study concludes that the GLIM criteria are effective in diagnosing malnutrition and predicting survival in patients with gastric cancer. Nutrition interventions significantly enhance survival outcomes, underscoring the importance of standardized nutrition treatments in improving patient prognosis.

Exploring patient stratification in head and neck squamous cell carcinoma using machine learning techniques: Preliminary results

BackgroundHead and Neck Squamous Cell Carcinoma (HNSCC) presents a significant challenge in oncology due to its inherent heterogeneity. Traditional staging systems, such as TNM (Tumor, Node, Metastasis), provide limited information regarding patient outcomes and treatment responses. There is a need for a more robust system to improve patient stratification. MethodIn this study, we utilized advanced statistical techniques to explore patient stratification beyond the limitations of TNM staging. A comprehensive dataset, including clinical, radiomic, genomic, and pathological data, was analyzed. The methodology involved correlation analysis of variable pairs and triples, followed by clustering techniques. ResultsThe analysis revealed that HNSCC subpopulations exhibit distinct characteristics, which challenge the conventional one-size-fits-all approach. ConclusionThis study underscores the potential for personalized treatment strategies based on comprehensive patient profiling, offering a pathway towards more individualized therapeutic interventions.

Bilateral Parotid Gland Oncocytoma Mimicking Oropharyngeal Cancer Metastasis: A Case Report from a Radiation Oncologist's Perspective.

Parotid oncocytomas typically present as benign, unilateral, slow-growing, painless, and solitary masses that are histologically firm and multilobulated. They are often misdiagnosed as pleomorphic adenomas, hemangiomas, or other forms of oncocytosis. However, in our case, the parotid oncocytomas initially mimicked bilateral parotid gland metastasis of advanced oropharyngeal cancer. Here, we present a case of oropharyngeal cancer with bilateral parotid oncocytomas treated with chemoradiotherapy (CCRT). We report the case of a 74-year-old man with a sore throat, neck pain, right earache, oropharyngeal cancer, and bilateral parotid gland oncocytoma. Head and neck computed tomography and magnetic resonance imaging (MRI) showed soft-tissue swelling in the right tonsillar fossa and several enlarged level II neck lymph nodes. MRI revealed enhancing masses in both parotid glands, initially suspected to be metastatic lymph nodes. A biopsy of the right palatine tonsil confirmed squamous cell carcinoma with human papilloma virus-16 positivity. A positron emission tomography scan was performed, and biopsy-proven malignant lesions were observed in the right tonsillar region with metastatic lymph nodes in the right and left neck. Focal hypermetabolism was observed in the parotid glands, suspected to be pathological lesions such as metastatic intra-parotid lymph node or Warthin's tumor. An ultrasonography-guided biopsy of the left parotid gland confirmed an oncocytoma. Based on these results, the patient was scheduled for CCRT. After pathological confirmation of parotid oncocytoma, CCRT was administered, excluding the parotid glands within the radiotherapy field. This is a case of bilateral parotid gland oncocytoma mimicking oropharyngeal cancer.

The heterogeneity of breast cancer metastasis: a bioinformatics analysis utilizing single-cell RNA sequencing data.

Breast cancer is a common malignancy in women, and its metastasis is a leading cause of cancer-related deaths. Single-cell RNA sequencing (scRNA-seq) can distinguish the molecular characteristics of metastasis and identify predictor genes for patient prognosis. This article explores gene expression in primary breast cancer tumor tissue against metastatic cells in the lymph node and liver using scRNA-seq. Breast cancer scRNA-seq data from the Gene Expression Omnibus were used. The data were processed using R and the Seurat package. The cells were clustered and identified using Metascape. InferCNV is used to analyze the variation in copy number. Differential expression analysis was conducted for the cancer cells using Seurat and was enriched using Metascape. We identified 18 distinct cell clusters, 6 of which were epithelial. CNV analysis identified significant alterations with duplication of chromosomes 1, 8, and 19. Differential gene analysis resulted in 17 upregulated and 171 downregulated genes for the primary tumor in the primary tumor vs. liver metastasis comparison and 43 upregulated and 4 downregulated genes in the primary tumor in the primary tumor vs lymph node metastasis comparison. Several enriched terms include Ribosome biogenesis, NTP synthesis, Epithelial dedifferentiation, Autophagy, and genes associated with epithelial-to-mesenchymal transitions. No single gene or pathway can clearly explain the mechanisms behind tumor metastasis. Several mechanisms contribute to lymph node and liver metastasis, such as the loss of differentiation, epithelial-to-mesenchymal transition, and autophagy. These findings necessitate further study of metastatic tissue for effective drug development.

Evaluation and Use of Natural Language Processing (NLP) Reasoning and Classification Models to Support Clinical Trial Patient Identification and Enrollment in the Community Oncology Setting

Clinical trial research in oncology relies heavily on clinical documentation within the electronic medical record (EMR) to ascertain patient eligibility in clinical trials based on inclusion and exclusion criteria. The structured data elements within the EMR serve as the primary information source for defining patient cohorts, with clinical cancer stage and performance status being two pivotal criteria determining trial eligibility. The challenge arises from the inconsistent availability of clinical stage and performance status data within the structured fields of the EMR despite their consistent presence in clinical notes. Additionally, there is a deficiency of standardization of this data that exists in the unstructured field. Hence, due to lack of structured data and standardization of said data, there are limitations in developing artificial intelligence (AI) models. To increase the comprehensiveness of clinical records, a clinical research team at a community oncology practice was consulted to identify requirements and extract essential clinical features from de-identified data. The methods outlined in this paper focused on eliminating false positives to allow future development of Large Language Models (LLM) using the outputted structured fields which resulted in an increase in patient record completeness with high accuracy. The accuracy ranged from 97.5-97.75% for the models that were developed. Out of the 60,000+ patients, the numerical staging, TNM (tumor, node, metastasis) staging, and Karnofsky performance score models added a structured field for 29.62%, 21.01%, and 40.64% patients respectively. Additionally, a semi-supervised NLP algorithm was applied on the performance status algorithm which achieved a mean absolute error (MAE) of 1.57. This work demonstrates the use case of natural language processing (NLP) in optimizing the clinical research enrollment process by providing an efficient and accurate method to detect key clinical values in unstructured patient data. Similar methodology with more advanced algorithms such as LLM can be employed to detect additional patient elements such as molecular biomarkers, imaging reports, postoperative surgical outcomes (i.e., clear margins etc.) and patient treatment outcomes using the extracted structured fields.

Exploring Multilingual Large Language Models for Enhanced TNM Classification of Radiology Report in Lung Cancer Staging

Background/Objectives: This study aimed to investigate the accuracy of Tumor, Node, Metastasis (TNM) classification based on radiology reports using GPT3.5-turbo (GPT3.5) and the utility of multilingual large language models (LLMs) in both Japanese and English. Methods: Utilizing GPT3.5, we developed a system to automatically generate TNM classifications from chest computed tomography reports for lung cancer and evaluate its performance. We statistically analyzed the impact of providing full or partial TNM definitions in both languages using a generalized linear mixed model. Results: The highest accuracy was attained with full TNM definitions and radiology reports in English (M = 94%, N = 80%, T = 47%, and TNM combined = 36%). Providing definitions for each of the T, N, and M factors statistically improved their respective accuracies (T: odds ratio [OR] = 2.35, p &lt; 0.001; N: OR = 1.94, p &lt; 0.01; M: OR = 2.50, p &lt; 0.001). Japanese reports exhibited decreased N and M accuracies (N accuracy: OR = 0.74 and M accuracy: OR = 0.21). Conclusions: This study underscores the potential of multilingual LLMs for automatic TNM classification in radiology reports. Even without additional model training, performance improvements were evident with the provided TNM definitions, indicating LLMs’ relevance in radiology contexts.

Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma.

To develop diagnostic models for differentiating gastric neuroendocrine carcinoma (g-NEC) and gastric mixed adeno-neuroendocrine carcinoma (g-MANEC) from gastric adenocarcinoma (g-ADC) based on traditional contrast enhanced CT imaging features and radiomics features. We retrospectively analyzed 90 g-(MA)NEC (g-MANEC and g-NEC) patients matched 1:1 by T-stage with 90 g-ADC patients. Traditional CT features were analyzed using univariable and multivariable logistic regression. Tumor segmentation and radiomics features extraction were performed with Slicer and PyRadiomics. Feature selection was conducted through univariable analysis, correlation analysis, LASSO, and multivariable stepwise logistic. The combined model incorporated clinical and radiomics predictors. Diagnostic performance was assessed with ROC curves and DeLong's test. The models' diagnostic efficacy was further validated in subgroup of g-NEC vs. g-ADC and g-MANEC vs. g-ADC cases. Tumor necrosis and lymph node metastasis were independent predictors for differentiating g-(MA)NEC from g-ADC (P < 0.05). The clinical model's AUC was 0.700 (training) and 0.667(validation). Five radiomics features were retained, with the radiomics model showing AUC of 0.809 (training) and 0.802 (validation). The combined model's AUCs were 0.853 (training) and 0.812 (validation), significantly outperforming the clinical model (P < 0.05). Subgroup analysis revealed that the combined model exhibited acceptable performance in differentiating g-NEC from g-ADC and g-MANEC from g-ADC, with AUCof0.887 and 0.823 in the training cohort and 0.852 and 0.762 in the validation cohort. A combined model based on traditional CT imaging and radiomic features provides a non-invasive and effective preoperative diagnostic method for differentiating g-(MA)NEC from g-ADC.

MiR-559 rs58450758 polymorphism is associated with colorectal cancer risk and prognosis in Chinese Han population.

Aim: This research examined the correlation between miR-559 rs58450758 and the clinical pathological characteristics and prognosis of CRC.Materials & methods: RT-qPCR was utilized to assess the miR-559 expression levels. Chi-square test was used to investigate the relationship between miR-559 and clinical features. The association between rs58450758 different genotypes and CRC risk, as well as clinical pathological parameters, was explored, utilizing logistic regression analysis and chi-square tests. The Cox regression model and Kaplan-Meier analysis evaluated overall survival in individuals with CRC.Results: The miR-559 was down-regulated in CRC patients' serum. The expressions of miR-559 were significantly associated with tumor size, differentiation, TNM stage and lymph node metastasis. The rs58450758 TT genotype and T allele carriers were more prevalent among CRC patients. The rs58450758 polymorphism was notably linked to tumor size, differentiation, TNM stage and lymph node metastasis in CRC patients. Furthermore, CC genotype carriers exhibited a longer survival period than CT/TT genotypes within the CRC population.Conclusion: The miR-559 rs58450758 polymorphism exhibits promise as a potential biomarker for prognosticating the outcomes of CRC.

Reduction of Blood Oxidative Stress Following Colorectal Cancer Resection

Background: Colorectal cancer is a major global health burden, with surgical resection being the standard treatment aimed at curative tumor removal. Oxidative stress plays a crucial role in colorectal cancer progression and prognosis. This study hypothesized that physical removal of colorectal cancer, a primary source of oxidative stress, would reduce blood levels of reactive oxygen metabolite derivatives (d-ROMs), a marker of oxidative stress, and biologic antioxidant potential (BAP) levels, a marker of antioxidant potential. Methods: This study included 123 patients who underwent radical resection for colorectal cancer. d-ROM and BAP levels were measured before and one month after surgery. Results: The clinicopathological analysis showed a correlation between preoperative d-ROM levels and tumor size (p &lt; 0.001). This study confirmed a significant reduction in d-ROM levels following tumor resection, indicating reduced systemic oxidative stress. The reduction was significant in stages II and III, but not in stage I. The d-ROM ratio before and after tumor resection was significantly higher in cases with positive lymph node metastasis and larger tumor size. BAP levels showed no significant changes post-surgery. Conclusions: These results suggest that d-ROMs could serve as a valuable biomarker for monitoring tumor burden and surgical efficacy in patients with colorectal cancer.

Quantitative detection of miR-25 for early diagnosis, postoperative assessment and TNM staging of pancreatic cancer

Objectives: Pancreatic cancer is one of the most common malignant tumors of the digestive tract. Due to its strong concealment and rapid disease progress, it is characterized by high mortality and low cure rate. Current research focuses on screening high-risk populations, preventing the occurrence of pancreatic cancer and developing imaging technology and tumor markers for early diagnosis. This study aimed to investigate the absolute quantitative detection of microRNA-25 (miR-25) and reveal its quantitative changes in the treatment of pancreatic cancer. We compared serum miR-25 level between pancreatic cancer patients and other tumor patients, especially those with gastrointestinal cancer, to provide further evidence for early diagnosis, differential diagnosis and prognosis of pancreatic cancer. Methods: We collected serum samples from 51 pancreatic cancer patients (including 21 patients with preoperative and postoperative samples), 52 pancreatitis patients, 141 other tumor patients, and 50 healthy individuals from Huashan Hospital, Fudan University. The serum levels of miR-25, Carbohydrate Antigen 19–9 (CA19–9), Carbohydrate Antigen 125 (CA125) and Carcinoembryonic Antigen (CEA) in these populations were measured to analyze the value of miR-25 quantitative detection in the diagnosis, postoperative assessment and Tumor Node Metastasis (TNM) staging of pancreatic cancer. Results: Among the 51 pancreatic cancer patients, 50 cases (98.04 %) showed miR-25 levels above the threshold (3333 copies/μl), while all samples in normal group showed negative. The mean level of miR-25 in serum was 5707.45 ± 361.02 copies/μl. In other tumor groups, 21/141 (14.89 %) patients showed positive results and the mean miR-25 level was 847.09 ± 125.97 copies/μl. Comparing before and after operation in 21 paired samples, the level of miR-25 declined significantly after operation, with an average decline rate of 86.36 %. Conclusions: Serum miR-25 levels were significantly higher in pancreatic cancer patients compared to both normal and other tumor groups and decreased significantly after surgery. In addition, miR-25 showed higher sensitivity than common tumor markers (CA19–9, CA125, CEA) in early diagnosis of pancreatic cancer, and proved to be of significant value in evaluating the effect of surgical treatment.

Risk stratification model for foreseeing overall survival in Chinese patients with initially metastatic small-cell lung cancer.

The study was outlined to develop and approve a nomogram and chance stratification demonstrate for foreseeing overall survival of Chinese patients with at first metastatic small-cell lung cancer (SCLC). We collected information from the Surveillance, Epidemiology, and End Results (SEER) database approximately Chinese SCLC patients with at first distant metastases between 2010 and 2015. Patients with incomplete data about the follow-up time or clinicopathological information were excluded. The included patients were randomized into the training and validation set. Univariate and multivariate Cox proportional hazard regression models were performed. By integrating the significant variables screened, a prescient nomogram and risk stratification model were developed. In addition, we collected 198 small-cell lung cancer patients with metastasis at diagnosis from the case database of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine as an external validation cohort. In all, 421 patients were screened from the SEER database. Multivariate examination showed that age (P = .049), sex (P = .001), grade (P = .008), chemotherapy (P = .001), liver metastasis (P = .001), and pleural invasion (P = .012) were independent prognostic factors. The C-indicator of the nomogram to anticipate overall survival was higher than that of the eighth edition of the American Joint Committee on Cancer Tumor Node Metastasis classification system (0.75 vs 0.543; P < .001). A risk stratification model was encouraged to be created to precisely classify patients into 2 prognostic bunches. The survival rates anticipated by the nomogram appeared to have critical qualifications from the Kaplan-Meier curves in the entire SEER cohort. Calibration curves and survival predictions also showed strong accuracy and consistency in the external validation cohort. The nomogram provided a clear prognostic superiority over the traditional Tumor Node Metastasis system. It could help clinicians make individual risk predictions for initially metastatic Chinese SCLC cancer patients and give necessary treatment recommendations.

Prognostic factors for intraductal papillary neoplasm of the bile duct following surgical resection: a systematic review and meta-analysis.

Intraductal papillary neoplasm of the bile duct (IPNB) is a biliary neoplasm characterized by intraductal papillary growth and varying degrees of malignant transformation. This study aimed to identify effective prognostic factors (PFs) for predicting the prognosis of IPNB after surgical resection, addressing the gap in the higher level evidence. We systematically searched databases from their inception to October 10, 2023. Data on 12 predetermined PFs were collected and subjected to a meta-analysis. Forest plots were used to summarize the findings. Fifteen studies with a total of 2311 patients were included. Among the PFs examined, extrahepatic tumor location (HR, 2.97; 95% CI 1.68-5.23), subclassification type 2 (HR, 2.62; 95% CI 1.45-4.76), R1 resection (HR, 2.47; 95% CI 1.73-3.51), elevated CA19-9 level (HR, 3.25; 95% CI 1.91-5.54), tumor multiplicity (HR, 2.65; 95% CI 1.40-5.02), and adjacent organ invasion (HR, 3.17; 95% CI 2.01-5.00) were associated with a poorer prognosis. Additionally, the combined HR values indicated that lymph node metastasis and poor tumor differentiation were linked to a worse prognosis, although both exhibited significant heterogeneity. Our study offers valuable insights for enhancing postoperative prognostication and treatment decision-making for IPNB patients with IPNB. These findings warrant further validation in future prospective studies.

CircLPHN3 correlates with prognosis in colorectal cancer and regulates cellular processes by targeting miR-142-5p.

Colorectal cancer (CRC) is often diagnosed late and has a poor prognosis. Circular RNAs (circRNAs) have been identified as prognostic biomarkers in various cancers, including CRC. The objective was to elucidate the role of circLPHN3 (hsa_circ_0069865) in CRC progression and to provide a promising prognostic marker for CRC. CircLPHN3 was identified through bioinformatics analysis of the GSE121842 dataset. The levels of circLPHN3 in CRC samples were analyzed by real time-quantitative polymerase chain reaction. Its clinical significance was assessed using the Kaplan-Meier curve and multivariate Cox regression. Downstream microRNAs of circLPHN3 were predicted with the RNAhybrid, Circular RNA Interactome, and starBase online databases. The target of miR-142-5p was predicted using miRDB, TargetScanHuman, starBase, and miRWalk databases. The relationship between circLPHN3, miR-142-5p, and LDB2 was verified by dual luciferase reporter assay. The function of circLPHN3 on CRC cell growth and metastasis was measured using Transwell and the cell counting kit-8 assay. Significant downregulation of circLPHN3 was found in CRC. CircLPHN3 was closely related to higher tumor node metastasis stage, lymph node metastasis, and predicted unfavorable prognosis. miR-142-5p was highly expressed in CRC and its expression was negatively regulated by circLPHN3. Overexpression of circLPHN3 curbed CRC cell growth, migration, and invasion, mediated by miR-142-5p. Moreover, LDB2 was identified as a target of miR-142-5p. CircLPHN3 acted as a prognostic biomarker and tumor suppressor for CRC via modulating miR-142-5p.

Prognostic value of miR-190a-5p in renal cell cancer and its regulatory effect on tumor progression.

As a usual malignant tumor in urinary system, renal cell cancer is regulated by microRNAs (miRNAs). This study revealed the prognostic value and regulatory effect of miR-190a-5p in renal cell cancer patients. A total of 253 renal cell cancer patients were included for prognostic value analysis. The target gene of miR-190a-5p was detected by luciferase reporter assay. Cell Counting Kit-8 analysis and Transwell analysis were performed to explore the proliferation, removal capability, and invasiveness of 786-0 and A498 cells. Prognostic value was calculated by Kaplan-Meier curve and Cox regression analysis. miR-190a-5p was more down-regulated in tumor tissues than in adjacent tissues. Renal cell cancer cases were differed as low and high groups ground on mean miR-190a-5p expression in tumor tissues. Overall survival probability was obviously high in patients with high miR-190a-5p level (log-rank test P = 0.011). Cox regression analysis revealed that miR-190a-5p expression (relative risk (RR) = 1.751, 95% confidence interval (CI) = 1.057-2.900, P = 0.030) and tumor node metastasis stage (RR = 1.719, 95% CI = 1.059-2.792, P = 0.028) were specialty indicators for poor renal cell cancer prognosis. GDF11 was directly targeting miR-190a-5p. Overexpressed miR-190a-5p could reduce the GDF11 expression, proliferation, removal capability, and invasiveness of renal cell cancer 786-0 and A498 cells. Elevated GDF11 could lead to a changeover of proliferation, removal capability, and invasiveness inhibition, which is induced by miR-190a-5p. miR-190a-5p was reduced in renal cell cancer tissues, and predicted worse outcomes of renal cell cancer cases. Overexpressed miR-190a-5p could restrain the proliferation, removal capability, and invasiveness of renal cell cancer cells via suppressing GDF11.

Lateral node metastasis in low rectal cancer as a hallmark to predict recurrence patterns.

Lateral node metastasis confers a poor prognosis in rectal cancer. Several multidisciplinary treatments have been proposed with favorable outcomes. However, appropriate neoadjuvant/adjuvant treatments or follow-up plans based on information about the probable recurrence site have not been specified. We aimed to clarify the distinctive features of recurrence patterns for lateral node-positive low rectal cancer according to the lateral and mesorectal lymph node status. We retrospectively analyzed 508 patients with stage III low rectal cancer who underwent lateral node dissection. We investigated the impact of lateral and mesorectal lymph node status on site-specific recurrence rates and patient survival. Analyses for relapse-free survival revealed the prognostic impact of lateral node positivity in stage III low rectal cancer (p < 0.0001). Lateral node-positive patients exhibited higher risk of overall recurrence, local recurrence, and recurrence in extra-regional nodes than lateral node-negative patients (p < 0.0001, p = 0.001, and p < 0.0001, respectively). However, lateral node positivity was not statistically associated with a hematogenous recurrence rate. In lateral node-positive patients, both tumor-node-metastasis (TNM)-N status and number of lateral nodes involved were revealed as significant prognostic factors (p < 0.0001, both). In addition, the number of lateral nodes involved could be a discriminatory indicator of probabilities of local recurrence and recurrence in extra-regional nodes (p = 0.02, and p < 0.0001, respectively). Lateral node-positive low rectal cancer exhibits higher local recurrence and extra-regional node recurrence rates that correlate with the number of lateral nodes involved.

Evaluation of the prognostic value of the new 9th edition Tumor-Node-Metastases (TNM) staging system for epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma patients with bone metastases

BackgroundThere are some changes in the new 9th edition Tumor-Node-Metastases (TNM) staging system for lung cancer, including subdividing M1c into M1c1 and M1c2 stage. The aim of this study was to assess the prognostic performance of the updated classification system and try to provide some real-world application data among advanced lung adenocarcinoma patients with bone metastases.MethodsAdvanced lung adenocarcinoma patients in M1c stage with bone metastases who receiving first-line first-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) and T790M-guided osimertinib as the second-line therapy were retrospectively screened from December 2016 to December 2021. A total of 126 patients were enrolled in this study. 62 patients and 64 patients were subdivided into M1c1 and M1c2 groups according to the 9th edition of TNM staging system.The first-line real-world progression-free survival (1LrwPFS), the second-line real-world progression-free survival (2LrwPFS), post-progression survival (PPS) and real-world overall survival (rwOS) were analyzed.ResultsThe overall median rwOS was 40.1 months (95% CI 35.996–44.204). 1LrwPFS was 13.9 months (95% CI 12.653–15.147) and 2LrwPFS was 14.5 months (95% CI 11.665–17.335) for all patients.Patients in M1c2 stage was inferior to M1c1 stage patients in rwOS (35.2 months vs. 42.9 months, HR = 0.512, P = 0.005). 2LrwPFS was moderately correlated with rwOS (r = 0.621, R2 = 0.568, P = 0.000). Multivariate analysis showed performance status (PS) score ≥ 2 and TP53 alteration positive were independent prognostic factors of worse rwOS.ConclusionsMore refined stratification of M1c according to the 9th edition of TNM staging system is conducive to the judgment of prognosis and the implementation of precision medicine for patients.

Expression of interleukin-8 and integrin β3 predicts prognosis of patients with hepatocellular carcinoma after hepatectomy.

As important components in the tumor microenvironment, interleukin-8 (IL-8) and integrin β3 play a key role in the progression and metastasis of hepatocellular carcinoma (HCC). This study aimed to determine the expression of IL-8 and integrin β3 and their prognostic value in patients with HCC after hepatectomy. We investigated the expression of IL-8 and integrin β3, their clinical significance, as well as their correlation in the cancer tissue of 130 patients with HCC using immunohistochemistry. The prognostic value of IL-8 and integrin β3 was investigated through the follow-up of patients with HCC after hepatectomy. In HCC, IL-8 expression had a positive correlation with integrin β3 expression. Increased expressions of IL-8 and integrin β3 were indicators of tumor progression and poor prognosis in patients with HCC after hepatectomy. IL-8 positive specimens exhibited a higher proportion of macrovascular invasion, larger tumor size, poor differentiation, and advanced tumor-node-metastasis (TNM) stage (P < .05, respectively). Integrin β3 positive group exhibited a higher proportion of TNM III-staged tumors (P < .05). The results indicated that macrovascular invasion, advanced TNM stage, and integrin β3 expression were independent unfavorable prognostic factors in HCC after hepatectomy. Integrin β3 expression was proved to be an independent unfavorable prognostic factor in HCC after hepatectomy. Targeting integrin β3 might be a potential therapeutic approach in preventing tumor progression in HCC.