Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus.

PURPOSE: To determine the optimal cut-off value of Ki-67 for predicting the survival of patients with clear cell renal cell carcinoma (ccRCC) and tumor thrombus and to explore the correlation between Ki-67 expression and pathological features. PATIENTS AND METHODS: We retrospectively analyzed Ki-67 immunohistochemical staining of ccRCC and tumor thrombus resected from February 2006 to February 2022. The survival rate was evaluated using the Kaplan-Meier method. The optimal cut-off value of the Ki-67 expression for predicting survival was determined by the minimum P-value method. Clinicopathological data were compared based on Ki-67 status (low versus high expression). Univariate and multivariate Cox regression analysis was used to explore independent predictors. RESULTS: A total of 202 patients (median age, 58 years [IQR, 52-65 years], 147 men) with ccRCC and tumor thrombus were included in the study. The optimal cut-off value of Ki-67 for predicting survival was 30%. 159 (78.7%) and 43 (21.3%) patients were included in the low-expression and high-expression groups. Patients with Ki-67 high expression had significantly worse recurrence-free survival (P < 0.001) and cancer-specific survival (P < 0.001). Ki-67 high expression was associated with adverse pathological features, including tumor necrosis, ISUP nuclear grade, sarcomatoid differentiation, perirenal fat invasion, renal pelvis invasion, and inferior vena cava wall invasion (all P < 0.050). Ki-67 expression ≥ 30% (P = 0.016), tumor side (P = 0.003), diabetes (P = 0.040), blood loss (P = 0.016), inferior vena cava wall invasion (P = 0.016), and sarcomatoid differentiation (P = 0.014) were independent predictors of cancer-specific survival. CONCLUSION: The optimal cut-off level of Ki-67 in predicting the prognosis of ccRCC and tumor thrombus was 30%. The high expression of Ki-67 was associated with the aggressive pathological phenotype and poor prognosis.

H&E and OCT4/CD34 for the assessment of lympho-vascular invasion in seminoma and embryonal carcinoma.

BACKGROUND: Lymphovascular invasion (LVI) is a relevant prognostic factor in germ cell tumors of the testis (GCTT), and it is included in the pT stage. However, its detection on hematoxylin and eosin (H&E) slides is very challenging, and previous studies reported fair to moderate inter-observer agreement among dedicated uropathologists. In the present study, we tested H&E and a recently developed in-house double staining for OCT4/CD34 to detect LVI in GCTT. METHODS: Nine authors [5 non-uropathologists and 4 uropathologists] independently evaluated 34 consecutive and retrospectively enrolled cases of GCTT. We assessed the inter-observer agreement (Fleiss's Kappa) with both H&E and OCT4/CD34. Besides, we compared the consensus diagnosis on both H&E and OCT4/CD34-stained sections with the original diagnosis to evaluate the pT re-staging (McNemar test) and identify the sources of disagreement. RESULTS: The inter-observer agreement among uropathologists plus non-uropathologists was fair with both H&E (KF=0.398; p < 0.001) and OCT4/CD34 (KF=0.312; p < 0.001). OCT4/CD34 (KF=0.290; p < 0.001) slightly reduces the inter-observer agreement compared to H&E (KF=0.321; p < 0.001) for non-uropathologists; in contrast, OCT4/CD34 (KF=0.293; p < 0.001) significantly reduces the inter-observer agreement compared to H&E (KF=0.529; p < 0.001) for uropathologists, changing it from moderate to fair. Consensus diagnosis with H&E modified the LVI status of the original diagnosis in 8/34 (23.5 %) cases (p: 0.070), with pT re-staging in 2/34 (5.9 %) cases (p: 0.500). Consensus diagnosis with OCT4/CD34 modified the LVI status of the original diagnosis in 8/34 (23.5 %) cases (p: 0.289), with pT re-staging in 3/34 (8.8 %) cases (p: 0.250). The consensus diagnosis with OCT4/CD34 modified the consensus diagnosis with H&E in 8/34 (23.5 %) cases (p: 0.727), and these findings resulted in pT-restaging in 3/34 (8.8 %) cases (p: 0.500). The sources of disagreement among uropathologists were: H&E [artefactual clefts misinterpreted as LVI in 4/6 (66.7 %) cases and true foci of LVI misinterpreted as clusters of histiocytes within the vessels in 2/6 (33.3 %) cases], OCT4/CD34 [artefactual clefts misinterpreted as LVI in 2/8 (25 %) cases, true LVI misinterpreted as artefactual clefts in 2/8 (25 %) cases or floaters in 4/8 (50 %) cases]. CONCLUSIONS: OCT4/CD34 does not improve the inter-observer agreement for the assessment of LVI in OCT4(+) GCTT. Consensus diagnosis with H&E modifies the LVI status in a significant number of cases, resulting in changes of the pT stage in a relatively small subgroup. Consensus diagnosis with OCT4/CD34 provides little additional benefit since it cannot exclude mimickers of LVI such as floaters and artefactual clefts. These results argue against the adoption of this diagnostic tool for the routine assessment of OCT4(+) GCTT.

ToMExO: A probabilistic tree-structured model for cancer progression.

Identifying the interrelations among cancer driver genes and the patterns in which the driver genes get mutated is critical for understanding cancer. In this paper, we study cross-sectional data from cohorts of tumors to identify the cancer-type (or subtype) specific process in which the cancer driver genes accumulate critical mutations. We model this mutation accumulation process using a tree, where each node includes a driver gene or a set of driver genes. A mutation in each node enables its children to have a chance of mutating. This model simultaneously explains the mutual exclusivity patterns observed in mutations in specific cancer genes (by its nodes) and the temporal order of events (by its edges). We introduce a computationally efficient dynamic programming procedure for calculating the likelihood of our noisy datasets and use it to build our Markov Chain Monte Carlo (MCMC) inference algorithm, ToMExO. Together with a set of engineered MCMC moves, our fast likelihood calculations enable us to work with datasets with hundreds of genes and thousands of tumors, which cannot be dealt with using available cancer progression analysis methods. We demonstrate our method's performance on several synthetic datasets covering various scenarios for cancer progression dynamics. Then, a comparison against two state-of-the-art methods on a moderate-size biological dataset shows the merits of our algorithm in identifying significant and valid patterns. Finally, we present our analyses of several large biological datasets, including colorectal cancer, glioblastoma, and pancreatic cancer. In all the analyses, we validate the results using a set of method-independent metrics testing the causality and significance of the relations identified by ToMExO or competing methods.

Biological considerations in the assessment of urothelial cancer: a retrospective.

In bladder cancer, variations in clinical course and treatment outcomes support the concept that the condition may comprise a compendium of different types of tumor diathesis with unique, albeit interrelated, pathways of development. This concept and the schema of developmental pathways of bladder cancer derived from it are intended to complement the traditional classification used to stage bladder cancer, providing a perspective on the potential evolution of a particular malignancy over time. The schema represents the intrinsic biologic potential of various types of bladder cancer. It also indicates a given tumor's likely behavior as can be predicted by its histopathologic appearance at a given point in time, what may be expected through specific interventions, how approaches to treatment may need to be adjusted in considering the pathway a specific tumor may follow, as well as how the disease course may reflect genetic changes associated with the generation of a specific malignant diathesis. These considerations and the concept of specific but interrelated pathways of development in bladder cancer are presented in their historical context and current clinical use.

Breast cancer: cured or not?

Survival following treatment of breast cancer may be estimated through the recognition of various prognostic factors. The Case Study presented here calls attention to several of these factors. The reliability and relative value of these prognosticators are discussed. Recommendations are offered for the practical application of prognostic information in the determination of expected mortality.

Statistical research needs in mechanistic modelling for carcinogenic risk assessment.

If the broad spectrum of mechanistic research conducted on an environmental carcinogen is to be used in quantifying cancer risks, statisticians must play a key role. Statistical methods are critically needed for a scientifically valid analysis of a complicated series of linked experimental findings. This will require a greater understanding of the underlying biology than is common in statistical consulting, aiding in the development of complicated mechanistically based mathematical descriptions of mean response and in the creation of statistical methods for the estimation of model parameters (e.g. likelihoods) able to use both the underlying model and much of the available data.

Carcinogenesis models for risk assessment.

This article provides an overview of different types of carcinogenesis models and discusses their use for risk assessment. One class of model, the multistage model, is especially suited for risk assessment purposes because it uses biological information about the process of carcinogenesis and the quantities of interest, such as time to tumour and number and size distribution of premalignant tumours, can be derived explicitly, allowing for standard statistical techniques to be used. The mathematical methods necessary for the treatment of multistage models are developed and the application of multistage models in risk assessment is discussed.