Risk stratification by pathological upstaging and tumor necrosis in clinical T1 clear-cell renal cell carcinoma: evidence from a multi-institutional cohort of 1081 patients.

Survival outcomes and establishment of a novel risk stratification system in patients with ovarian yolk sac tumors

To identify prognostic factors that guide adjuvant therapy decisions, we investigated factors predicting recurrence in patients with high-risk clear cell renal cell carcinoma (RCC) after nephrectomy. We retrospectively reviewed patients with non-metastatic, high-risk clear cell RCC who underwent radical or partial nephrectomy at our institution and affiliated centers between January 2016 and March 2024. Multivariate analysis using the Cox proportional hazards model was performed to identify clinicopathological factors associated with recurrence. On the basis of these factors, we developed a risk stratification model. A total of 338 patients were included. The 5-year recurrence-free survival (RFS) rate was 54.3%. Multivariate analysis identified a body mass index of ≤ 22kg/m2 (Hazard Ratio [HR]: 2.61), rhabdoid differentiation (HR: 5.14), anemia (HR: 1.97), hypercalcemia (HR: 2.67), and C-reactive protein ≥ 0.5mg/dL (HR: 1.72) as independent predictors of recurrence. RFS was significantly different between patients with varying numbers of risk factors: 3-year RFS rates were 22.6% for those with 3-4 factors, 47.9% for those with two, 75.5% for those with one, and 83.6% for those with none. We identified independent predictors of recurrence in patients with nephrectomy-treated clear cell RCC. Patients stratified according to a risk score based on these factors had different recurrence rates, suggesting that this score could assist in guiding adjuvant therapy decisions.

Purpose: To investigated the prognostic significance of the geriatric nutritional risk index (GNRI) in patients with surgically treated clear cell renal cell carcinoma (ccRCC).Patients and methods: We retrospectively selected 4,591 consecutive patients with surgically treated ccRCC from a multi-institutional Korean collaboration between 1988 and 2015. The clinical significance of the GNRI as a continuous and categorical variable was determined.Results: Preoperative low GNRI was significantly associated with older age, low body mass index, presence of diabetes, poor performance status, and presence of symptoms at diagnosis, as well as pathologic features such as aggressive tumor characteristics including large tumor size, advanced stage, high nuclear grade, lymphovascular invasion, sarcomatous differentiation, and tumor necrosis. A low GNRI was significantly associated with a short recurrence-free survival (RFS) in localized (pT1-2N0M0) ccRCC and cancer-specific survival (CSS) in the entire cohort, and with short RFS and CSS in the subgroup analysis according to age categories (≤65 and >65 years). Multivariate Cox regression analysis showed that preoperative GNRI, as a continuous or categorical variable, was an independent predictor of RFS and CSS.Conclusion: Malnutrition as assessed by the preoperative GNRI is associated with aggressive tumor characteristics and poor survival in patients with surgically treated ccRCC.

Prognostic Impact of Preoperative Neutrophil-to-Lymphocyte Ratio in Localized Nonclear Cell Renal Cell Carcinoma

Novel Biomarkers Predict Outcome in Patients With HPV-Negative Squamous Cell Carcinoma of the Oropharynx: Survivorship

Background Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. Methods A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. Results The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. Conclusion These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

BackgroundT4 tumor, lymphovascular invasion (LVI) and perineural invasion (PNI) are regarded as one of risk factors and associated with poor outcomes in colorectal cancer. The relationship between these three combined risk factors and the prognosis for colon cancer is not yet clear. The purpose of this study was to evaluate the prognostic value of combining the risk factors T4 tumor, LVI, and PNI in stage II–III colon cancer.MethodsBetween January 2011 and December 2019, we retrospectively reviewed the medical records of patients who underwent curative resection for stage II–III colon cancer at four Hallym University-affiliated hospitals. These patients are categorized into three groups based on T4, LVI and PNI: no-risk group (no risk factors), low-risk group (one risk factor), and high-risk group (two or more risk factors).ResultsOf 1684 patients, the incidence of no-, low-, and high-risk group were 49.3%, 32.6%, 18.0%, respectively. The median follow-up period was 48.9 months, and the 5-year recurrence-free survival (RFS) rate decreased from 78.5% to 58.7% as the number of risk factors increased (P < 0.001). Cox’s proportional hazard regression models showed that T4 (P < 0.001), LVI (P = 0.043), and PNI (P = 0.018) were independent prognostic factors for poor RFS. In subgroup analysis in stage II colon cancer, patients with one or more risk factors showed the better 5-year RFS rate when they received adjuvant chemotherapy than in those who did not (P < 0.001). Poor/mucinous differentiation, obstruction, and lymph-node positivity were independent predictors in the high risk group.ConclusionThe present study showed the histological combination of LVI, PNI, and T4 indicates a poor prognosis for RFS in patients with stage II–III colon cancer. Therefore, patients with one of these risk factors should be considered for chemotherapy and have close follow-up.

Evidence for American Thyroid Association (ATA) risk stratification stems largely from studies involving patients undergoing total thyroidectomy. We aimed to assess the risk of recurrence according to the present ATA risk stratification system in patients who underwent lobectomy. Retrospective cohort study. Patients who underwent thyroid lobectomy for 1-4cm-sized papillary thyroid carcinoma (n=571). Disease-free survival (DFS) was compared according to the ATA risk stratification, and specific lymph node (LN) characteristics were evaluated to modify the ATA criteria with a higher predictability for recurrence. Based on the ATA risk stratification, 439 patients (61.1%) were classified into intermediate- or high-risk group, and consideration for completion thyroidectomy is suggested by ATA guidelines for these patients. However, no significant differences were found in DFS among the low-, intermediate- and high-risk groups (P=.9). In contrast, when patients were stratified according solely to the LN criteria from the ATA risk stratification, only 127 patients (22.2%) had intermediate risk (intermediate-N1a) and exhibited significantly poorer DFS than those with N0 disease (P=.035). Modifying the intermediate-N1a criteria by adding the extranodal extension (ENE) status and omitting the clinical nodal disease enabled the subclassification of 19 patients (3%) with a high risk for recurrence. The present study suggests that risk stratification based solely on LN metastases is more reasonable for predicting structural persistence/recurrence following lobectomy than that based on the overall ATA criteria. Considering the ENE status can assist in selecting patients with a high risk of recurrence to minimize further treatments.

Given that myc was known to be a cancer-causing gene in several cancers including kidney renal clear cell carcinoma (KIRC). We aimed to construct myc-regulated genes (MRGs)-based prognostic signature. We obtained the mRNA expression and clinical data of KIRC from The Cancer Genome Atlas (TCGA) database and MRGs from the Molecular Signature Database (MSigDB). Then, a prognostic signature consisting of 8 MRGs (IRF9, UBE2C, YBX3, CDKN2B, CKAP2L, CYFIP2, FBLN5, and PDLIM7) was developed by differential expression analysis, cox regression analysis, and least absolute shrinkage and selection operator (lasso) analysis. Patients with KIRC were divided into high- and low-risk groups based on risk scores of MRGs-based signatures. Patients in the high-risk group showed inferior clinical characteristics and survival. In addition, the risk score was an independent prognostic factor for KIRC, and the risk score=based nomogram displayed satisfactory performance to predict the survival of KIRC. The MRGs-based signature is also correlated with immune cell infiltration and the mRNA expression of important immune checkpoints (IDO2, PDCD1, LAG3, FOXP3, and TIGIT). The tumor mutation burden (TMB) landscape between the high- and low-risk groups showed higher levels of TMB in the high-risk group than in the low-risk group and that higher levels of TMB predicted a poorer prognosis in KIRC. Furthermore, patients with KIRC in the high-risk group are more likely to experience immune escape. At last, we found patients with KIRC in the high-risk group were more sensitive to several chemotherapy drugs such as sunitinib, gefitinib, nilotinib, and rapamycin than patients with KIRC in the low-risk group. Our study successfully constructed and validated an MRGs-based signature that can predict clinical characteristics, prognosis, level of immune infiltration, and responsiveness to immunotherapy and chemotherapy drugs in patients with KIRC.

Objective To explore the long-term OS and recurrence-free survival (RFS) and the influencing factors in breast cancer patients. Methods According to the inclusion and exclusion criteria, a total of 2 423 breast cancer patients who underwent breast surgery in the Department of Breast Surgery, Fifth Medical Center, General Hospital of PLA from January 1, 2000 to December 31, 2015 were enrolled for a retrospective study. Kaplan-Meier method and log-rank test were used to compare the 5-year OS and RFS among patients with different clinical stages, molecular subtypes and surgical methods. Cox proportional hazard regression model was used to analyze the influencing factors on the patient survival. Results In 2 423 cases of breast cancer, the median age was 48 years, the median follow-up time was 5.2 years (range: 3.5-18.7 years) and the follow-up rate was 85.3%(2 066/2 423). The 5-year and 10-year OS rate was 91.5% and 84.4% respectively, and the 5-year and 10-year RFS rate (except stage Ⅳ breast cancer) was 85.8% and 78.4% respectively. As for clinical stage, the operable breast cancer accounted for 81.0% (1 963/2 423), local advanced breast cancer 15.6%(378/2 423)and stage Ⅳ breast cancer 3.4%(82/2 423). The 5-year OS rate in stage 0, Ⅰ, Ⅱ, Ⅲ and Ⅳ breast cancer was 100%, 98.5%, 93.8%, 78.1% and 50.8%, respectively, and the 5-year RFS rate (except stage Ⅳ breast cancer) was 98.5%, 95.4%, 87.0% and 63.0%, respectively. Clinical stage was significantly correlated with the 5-year OS and RFS rate of patients (χ2=356.067, 250.433, both P<0.001). As for molecular subtype, except 205 patients with unknown molecular type, the remaining 2 218 patients were divided into luminal, HER-2 overexpression and triple-negative subtypes according to the receptor status, accounting for 72.3%(1 604/2 218), 10.1%(225/2 218) and 17.5%(389/2 218), respectively. The 5-year OS rate of luminal, HER-2 overexpression and triple-negative subtypes was 93.1%, 88.3% and 84.4%, respectively, and the 5-year RFS rate (except stage Ⅳ breast cancer) were 87.7%, 84.8% and 76.7%, respectively. The 5-year OS and RFS rate presented a significant difference across three groups (χ2=24.124, 31.668, both P<0.001). As for surgical methods, the breast-conserving rate was 24.8% (600/2 423) in all patients. In stage Ⅰ breast cancer, the breast-conserving rate was 44.9%(309/688); the breast-conserving surgery group had a higher 5-year OS rate compared with mastectomy group (99.3% vs 98.4%, χ2=6.338, P=0.012); however the 5-year RFS rate showed no significant difference between two groups (96.7% vs 94.8%, χ2=2.245, P=0.134). In stage Ⅱ breast cancer, the breast-conserving rate was 21.1%(237/1 125), the 5-year OS rate in breast-conserving surgery group and mastectomy group was 97.2% and 92.7%, respectively and the 5-year RFS rate was 88.5% and 87.1%, respectively, indicating no significant difference between two groups (χ2=3.793, 1.425; P=0.051, 0.233). Cox proportional hazard regression analysis showed that age, clinical stage and molecular subtype were correlated with the OS of breast cancer patients (HR=1.017, 95%CI: 1.004-1.029, P=0.019; HR=3.242, 95%CI: 2.763-3.803, P<0.001, HR=1.203, 95%CI: 1.066-1.357, P=0.003). Conclusions Age, clinical stage and molecular subtypes are prognostic factors for breast cancer. In stage Ⅰ-Ⅱ breast cancer, the efficacy of breast-conserving surgery is superior to or not worse than mastectomy. Key words: Breast neoplasms; Survival rate; Neoplasm recurrence, local; Breast conserving surgery

Purpose To determine if sex differences in abdominal visceral fat composition, measured by using computed tomography (CT), and tumor glucose metabolism, measured by gene expression, can help predict outcomes in patients with clear cell renal cell carcinoma (RCC). Materials and Methods This retrospective cohort study included 222 patients with clear cell RCC from The Cancer Imaging Atlas. By using CT, body fat was segmented into subcutaneous fat and visceral fat areas (VFAs) and normalized to total fat to obtain the relative VFA (rVFA) and relative subcutaneous fat area. Multivariate Cox proportional hazard regression models were performed to identify effects of rVFA on sex-specific survival. Expression profiles for 39 glycolytic genes in tumors from these patients were obtained from The Cancer Genome Atlas to determine sex differences in metabolism and compared with rVFA. Key mutations in clear cell RCC were analyzed for association with rVFA and tumor glycolytic profiles. Results Women with rVFA greater than 30.9% had an increased risk of death (hazard ratio, 3.66 [95% confidence interval: 1.64, 8.19]) for women vs 1.13 ([95% confidence interval: 0.58, 2.18] for men, P = .028). Glycolytic gene expression stratified both men and women, and the combination of low rVFA and low glycolysis identified 19 women with excellent overall survival (P < .001). SETD2 and BAP1 mutations were uniquely enriched in female tumors with high glycolysis (P = .036 and .001, respectively). No significant differences were identified in tumor mutations between patients with high and low rVFA. Conclusion Sex differences in visceral fat and tumor glucose metabolism may provide a new risk-stratification system for patients with clear cell RCC. © RSNA, 2018 Online supplemental material is available for this article.

Caspases are the main point in the apoptotic process. We have collected some information from 210 cases of Ductal breast cancer (pT1 - pT2) such as tumour size, histological differentiation degree, lymph node status and tumor necrosis in the infiltrating component and we have evaluated the number of apoptotic cells or bodies by TUNEL technique as well as immunohistochemical studies to evaluate the expression of caspase 3 and caspase 6, and proliferation index. Our results show that lymph node status and cell atypism are independent prognostic factors for recurrence and mortality and only tumour size is an independent prognostic factor for recurrence. However, the apoptotic index and the immunohistochemical expression of caspases and cell proliferation index have not turned out to be independent prognostic factors neither for recurrence nor mortality. These results show that classic prognostic factors known until now are the most important factors to predict the evolution of the illness.

Kidney renal clear cell carcinoma (KIRC) is one of the common malignant tumors of the urinary system. Patients with different risk levels are other in terms of disease progression patterns and disease regression. The poorer prognosis for high-risk patients compared to low-risk patients. Therefore, it is essential to accurately high-risk screen patients and gives accurate and timely treatment. Differential gene analysis, weighted correlation network analysis, Protein–protein interaction network, and univariate Cox analysis were performed sequentially on the train set. Next, the KIRC prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO), and the Cancer Genome Atlas (TCGA) test set and the Gene Expression Omnibus dataset verified the model’s validity. Finally, the constructed models were analyzed; including gene set enrichment analysis (GSEA) and immune analysis. The differences in pathways and immune functions between the high-risk and low-risk groups were observed to provide a reference for clinical treatment and diagnosis. A four-step key gene screen resulted in 17 key factors associated with disease prognosis, including 14 genes and 3 clinical features. The LASSO regression algorithm selected the seven most critical key factors to construct the model: age, grade, stage, GDF3, CASR, CLDN10, and COL9A2. In the training set, the accuracy of the model in predicting 1-, 2- and 3-year survival rates was 0.883, 0.819, and 0.830, respectively. The accuracy of the TCGA dataset was 0.831, 0.801, and 0.791, and the accuracy of the GSE29609 dataset was 0.812, 0.809, and 0.851 in the test set. Model scoring divided the sample into a high-risk group and a low-risk group. There were significant differences in disease progression and risk scores between the two groups. GSEA analysis revealed that the enriched pathways in the high-risk group mainly included proteasome and primary immunodeficiency. Immunological analysis showed that CD8 (+) T cells, M1 macrophages, PDCD1, and CTLA4 were upregulated in the high-risk group. In contrast, antigen-presenting cell stimulation and T-cell co-suppression were more active in the high-risk group. This study added clinical characteristics to constructing the KIRC prognostic model to improve prediction accuracy. It provides help to assess the risk of patients more accurately. The differences in pathways and immunity between high and low-risk groups were also analyzed to provide ideas for treating KIRC patients.

Background Kidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear. Methods We extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package “glmnet.” Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis. Results We found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. Risk score=AC015813.1∗(0.0086)+EMX2OS∗(−0.0101)+LINC00173∗(0.0309)+PWAR5∗(−0.0146)+SNHG1∗(0.0043). The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628. Conclusions In conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.

BackgroundStudies over the past decade have shown that long non-coding RNAs (lncRNAs) play an essential role in the tumorigenesis and progression of kidney renal clear cell carcinoma (KIRC). Meanwhile, autophagy has been demonstrated to regulate KIRC pathogenesis and targeting therapy resistance. However, the prognostic value of autophagy-related lncRNAs in KIRC patients has not been reported before.MethodsIn this study, we obtained transcriptome data of 611 KIRC cases from the TCGA database and 258 autophagy-related mRNAs from the HADb database to identify autophagy-related lncRNAs by co-expression network. A prognostic model was then established basing on these autophagy-related lncRNAs, dividing patients into high-risk and low-risk groups. Survival analysis, clinical variables dependent receiver operating characteristic (ROC) analyses, univariate/multivariate Cox analyses, and clinical correlation analysis were performed based on risk signature with R language. Gene set enrichment analysis (GSEA) was then performed to investigate the potential mechanism of the risk signature promoting KIRC progression with GSEA software. CIBERSORT algorithm was performed to assess the impact of these lncRNAs on the infiltration of immune cells.ResultsA total of 17 lncRNAs were screened out and all these lncRNAs were found significantly related to KIRC patients’ overall survival in subsequent survival analyses. Besides, the overall survival time in the high-risk group was much poorer than in the low-risk group. The ROC analysis revealed that the prognostic value of risk signature was better than age, gender, grade, and N stage. Univariate/multivariate analyses suggested that the risk signature was an independent predictive factor for KIRC patients. Immune and autophagy related pathways were dramatically enriched in high-risk and low-risk groups, respectively, and lncRNAs related immune cells were identified by CIBERSORT.ConclusionsIn summary, our identified 17 autophagy-related lncRNAs had prognostic value for KIRC patients which may function in immunomodulation.