UNASSIGNED: Frozen shoulder (FS) is a common disorder causing shoulder pain and limited motion. Magnetic resonance imaging (MRI) is expected to help diagnose FS and realize the disease stage if stage-specific features are present. We aimed to survey stage-related MRI findings of FS in the literature.
UNASSIGNED: MEDLINE, SCOPUS, and Google Scholar databases were searched with search terms \"frozen shoulder\" or \"adhesive capsulitis\" combined with \"magnetic resonance imaging.\" Studies that discussed MRI findings in relation to FS stages were retrieved. The course of FS was divided into stages 1 to 4 according to Hannafin and Chiaia.
UNASSIGNED: Two of the noncontrast-enhanced MRI findings were stage-related. T2 signal hyperintensity of the joint capsule was more frequent in stages 1 and 2. The axillary capsule thickness was greater in stages 1 and 2. However, these findings were also seen in the later stages to a lesser degree. Effusion around the long head of biceps, subcoracoid fat obliteration, and coracohumeral ligament thickening were common in FS but their relation to the stages was not evident. Signal enhancement on contrast-enhanced MRI was not consistently linked to stages.
UNASSIGNED: T2 signal hyperintensity and axillary capsule thickening are characteristic of the early stages of FS, although MRI alone cannot completely define the disease stage.

Treatment of rare/ultra-rare tumors is an unmet need due to a lack of standardized therapies and clinical trials. We developed the Molecular Tumor Board (MTB), a multidisciplinary team that integrates molecular profiling to generate personalized, N-of-One treatments for advanced cancers. This study evaluates 112 patients with rare/ultra-rare tumors who presented to the MTB and were evaluable for clinical therapeutic outcome. Overall, 46/112 patients (41%) received a treatment regimen with a high degree of matching between tumor molecular alterations and drugs given (reflected by a high Matching Score (≥50%)). Patients with a high versus low Matching Score experienced significantly longer progression-free survival (p = 0.005) and overall survival (p = 0.047), and higher rates of clinical benefit (stable disease ≥6 months, partial response, or complete response) (54% vs. 32% p = 0.027). The MTB facilitated personalized N-of-One matching of drugs to tumor molecular alterations, which was associated with improved clinical outcomes in patients with rare/ultra-rare cancers.

BACKGROUND: Clinical staging in lung cancer has implications for treatment planning and prognosis. We sought to determine the rate of inaccurate clinical stage (relative to pathologic), identify risk factors for inaccuracy, and evaluate the association of inaccuracy on survival. We hypothesized that inaccurate staging was associated with poor survival.
METHODS: In this retrospective cohort study, adult patients who received surgical resection without neoadjuvant treatment for nonsmall cell lung cancer from 2004 to 2020 in the National Cancer Database were categorized by accuracy of clinical stage (relative to pathologic stage). Multivariate models were used to determine risk factors for inaccuracy. The association between inaccuracy and overall survival was also analyzed.
RESULTS: We identified 255,598 patients with lung cancer, including 84,543 patients (33.1%) who were inaccurately staged. Stage inaccuracy was associated with higher tumor, node, metastasis stage (T-category 3: odds ratio [OR] = 1.2, 95% confidence interval [CI] 1.15-1.28; N-category 2: OR = 2.6, 95% CI 2.47-2.79), greater quantity of lymph nodes evaluated, and more extensive resection (extended lobectomy/bilobectomy: OR = 1.3, 95% CI 1.20-1.37; pneumonectomy: OR = 1.6, 95% CI 1.54-1.74). Patients undergoing robotic surgery were less likely to be inaccurately staged (OR = 0.89, 95% CI 0.852-0.939). Inaccurate staging was associated with worse overall survival (5-y 67.5% accurate versus 55.4% inaccurate, P < 0.001). Inaccurate staging was also associated with worse survival in a multivariate Cox model (hazard ratio [HR] = 1.3, 95% CI 1.29-1.33). Both \"understaging\" (path > clinical) and \"overstaging\" (clinical > path) were associated with inferior survival.
CONCLUSIONS: Inaccurate clinical stage (relative to pathologic) occurs in one-third of patients receiving surgery for lung cancer. Inaccuracy is associated with poor survival. Quality improvement initiatives should focus on improving clinical staging accuracy.

Breast cancer, as the most common cancer, has surpassed lung cancer worldwide. The neutrophil-to-lymphocyte ratio (NLR) has been linked to the onset of cancer and its prognosis in recent studies. However, quite a few studies have shown that there is a link between NLR and lymph node metastases in cN0 hormone receptor-positive (HR(+)) breast cancer. The purpose of this study was to evaluate the correlation between NLR and lymph node metastases in cN0 HR(+) breast cancer patients. From January 2012 to January 2022, 220 patients with cN0 HR(+) invasive breast cancers were enrolled in this study. The relationship between NLR and pathological data was statistically examined. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff of NLR, a chi-squared test was used for the univariate analysis, and logistic analysis was used for the multivariate analysis. The NLR had an optimal cutoff of 2.4 when the Jorden index was at a maximum. Patients with axillary lymph node metastases had a higher NLR (P < 0.05). A Univariate analysis showed that there were significant differences in cN0 HR(+) breast cancer with axillary lymph node metastasis among different clinical stages, histological grades, Ki-67 levels, tumor sizes, and NLR levels (P < 0.05). Clinical stage, tumor size, and NLR were found to be independent risk factors for lymph node metastases in multifactorial analysis. In cN0 HR(+) breast cancer, NLR is an independent risk factor for lymph node metastases. An NLR ≥ 2.4 indicates an increased probability of lymph node metastases. An elevated preoperative NLR has a high predictive value for axillary lymph node metastases.

BACKGROUND: This study explored the predictors of upstaging and multiple sites of extension, and constructed a predictive model based on perioperative characteristics to calculate the risk of upstaging of cT1 renal cell carcinoma to pT3.
METHODS: We retrospectively reviewed 1012 patients diagnosed with cT1 renal cell carcinoma who underwent surgical treatment at the Affiliated Hospital of Qingdao University between June 2016 and August 2021. The continuous and categorical variables were analyzed using the Mann-Whitney U test and Chi-square test, respectively. After randomly dividing patients into a training set and an internal validation set with a ratio of 7:3, univariate and multivariate logistic regression analyses were used to explore the predictors of upstaging and multiple sites of extension. A nomogram model was established based on the predictors of upstaging and was validated.
RESULTS: Ninety-one cases (8.99%) of renal cell carcinoma were upstaged to pT3. In the training set, multivariate logistic regression identified the following predictors of upstaging: maximum tumor diameter, hilus involvement, tumor necrosis, tumor edge irregularity, symptoms, smoking, and platelet-lymphocyte ratio. A nomogram model was established based on the predictors. The area under the receiver operating characteristic curve was 0.810 in the training set, and 0.804 in the validation set. A 10-fold internal cross-validation conducted 200 times showed that the mean area under the curve was 0.797. The calibration curve and decision curve analysis suggested that the nomogram had robust clinical predictive power. Analyses showed higher neutrophil-lymphocyte ratio and tumor necrosis were associated with multiple sites of extrarenal extension in patients with pT3a renal cell carcinoma.
CONCLUSIONS: We identified 7 predictors of upstaging to pT3 and 2 predictors of multiple sites of extension. A nomogram model was constructed with satisfactory accuracy for predicting upstaging to pT3.

BACKGROUND: The primary tumor (T) component in the eighth edition of pleural mesothelioma (PM) staging system is based on pleural involvement and extent of invasion. Quantitative assessment of pleural tumor has been found to be prognostic. We explored quantitative and qualitative metrics to develop recommendations for T descriptors in the upcoming ninth edition of the PM staging system.
METHODS: The International Association for the Study of Lung Cancer prospectively collected data on patients with PM. Sum of maximum pleural thickness (Psum) was recorded. Optimal combinations of Psum and eighth edition cT descriptors were assessed using recursive binary splitting algorithm, with bootstrap resampling to correct for the adaptive nature of the splitting algorithm, and validated in the eighth edition data. Overall survival (OS) was calculated by the Kaplan-Meier method and differences in OS assessed by the log-rank test.
RESULTS: Of 7338 patients submitted, 3598 were eligible for cT analysis and 1790 had Psum measurements. Recursive partitioning identified optimal cutpoints of Psum at 12 and 30 mm, which, in combination with extent of invasion, yielded four prognostic groups for OS. Fmax greater than 5 mm indicated poor prognosis. cT4 category (based on invasion) revealed similar performance to eighth edition. Three eighth edition descriptors were eliminated based on low predictive accuracy. Eighth edition pT descriptors remained valid in ninth edition analyses.
CONCLUSIONS: Given reproducible prognostication by Psum, size criteria will be incorporated into cT1 to T3 categories in the ninth edition. Current cT4 category and all pT descriptors will be maintained, with reclassification of fissural invasion as pT2.

UNASSIGNED: MicroRNAs (miRNAs) are key regulators of gene expression that have been implicated in gynecological and breast cancers. Understanding the cancer stage-wise expression patterns of miRNAs and their interactions with other RNA molecules in cancer is crucial to improve cancer diagnosis and treatment planning. Comprehensive web tools that integrate data on the transcriptome, circulating miRNAs, and their validated targets to derive beneficial conclusions in cancer research are lacking.
UNASSIGNED: Using the Shiny R package, we developed a web tool called ExplORRNet that integrates transcriptomic profiles from The Cancer Genome Atlas and miRNA expression data derived from various sources, including tissues, cell lines, exosomes, serum, and plasma, available in the Gene Expression Omnibus database. Differential expression analyses between normal and tumor tissue samples as well as different stages of cancer, accompanied by gene enrichment and survival analyses, can be performed using specialized R packages. Additionally, a miRNA-messenger RNA (mRNA)-long non-coding RNA (lncRNA) networks are constructed to identify regulatory modules.
UNASSIGNED: Our tool identifies cancer stage-wise differentially regulated miRNAs, mRNAs, and lncRNAs in gynecological and breast cancers. Survival analysis identifies miRNAs associated with patient survival, and functional enrichment analysis provides insights into dysregulated miRNA-related biological processes and pathways. The miRNA-mRNA-lncRNA networks highlight interconnected regulatory molecular modules driving cancer progression. Case studies demonstrate the utility of the ExplORRNet for studying gynecological and breast cancers.
UNASSIGNED: ExplORRNet is an intuitive and user-friendly web tool that provides a deeper understanding of dysregulated miRNAs and their functional implications in gynecological and breast cancers. We hope our ExplORRNet tool has potential utility among the clinical and basic researchers and will be beneficial to the entire cancer genomics community to encourage and facilitate mining the rapidly growing public databases to progress the field of precision oncology. The ExplORRNet is available at https://mirna.cs.ut.ee.

UNASSIGNED: To determine whether galectin-9 gene (LGALS9) expression is correlated with cervical cancer progression, clinicopathological characteristics, and overall survival. To determine the biological processes and the abundance of tumour infiltrating immune cells related to the expression of LGALS9.
UNASSIGNED: The study was conducted in two phases: 1) The expression level of LGALS9 was determined using the data of 193 squamous cell carcinoma (SCC) samples from The Cancer Genome Atlas (TCGA) database. Biological processes and tumour infiltrating cells associated to LGALS9 expression were evaluated using gene set enrichment analysis (GSEA) and tumour immune estimation resource (TIMER). 2) Independently, galectin-9 was identified in 40 SCC samples by immunohistochemistry and optical density quantified using ImagePro® software.
UNASSIGNED: The LGALS9 gene showed increased expression in cervical cancer samples. A higher expression level in SCC was related to better overall survival and to early clinical stages. GSEA showed that tumours with higher expression of LGALS9 were enriched in immune pathways such as interferon_alpha_response, and complement, the analysis of TIMER database showed a positive correlation between the expression level of LGALS9 and the abundance of tumour infiltrating immune cells. In addition, higher expression of galectin-9 was found in biopsies of SCC patients at early clinical stages, showing a trend of better survival.
UNASSIGNED: Higher expression levels of LGALS9 and galectin-9 in SCC were related to early clinical stages and better prognosis. GSEA and TIMER analysis suggested that galectin-9 could play an antitumor role in cervical SCC.

OBJECTIVE: Real-life estimations of survival by stage in colorectal cancer are scanty. We estimated population-based net survival by pathological stage and location, and for rectal cancer by patterns of evolution according to clinical and pathological stage with regard to neoadjuvant therapy.
METHODS: Age-standardized net survival was estimated on 19,630 colorectal cancers diagnosed between 2009 and 2015.
RESULTS: Five-year net survival was 64 % for colon and 62 % for rectal cancer. The highest absolute difference between colon and rectum was 12 % for stage II women aged 75 (91% vs. 79 %). Among patients with clinical stage III rectal cancer, 67 % no longer had pathological node involvement after neoadjuvant treatment. Survival was similar in clinical stage I, II or III and pathological stage III after neoadjuvant treatment and in pathological stage III without neoadjuvant treatment (between 67 % and 72 %). It ranged between 80 and 82 % in pathological stage II, without neoadjuvant treatment or with clinical stage I, II or III before neoadjuvant treatment. Survival ranged between 93 % and 95 % in pathological stage I, treated with surgery only or with clinical stage II or III before neoadjuvant treatment.
CONCLUSIONS: Prognosis is associated with stage determined on surgical specimens rather than stage at the initial workup.

[This corrects the article DOI: 10.3389/fimmu.2023.1222428.].