Donald E. Henson

Cystadenomas of the liver and extrahepatic bile ducts☆ Morphologic and immunohistochemical characterization of the biliary and intestinal variants

Cystadenomas of the liver and extrahepatic bile ducts (EHBD) are uncommon but distinctive neoplasms whose terminology and epithelial phenotype have been a source of controversy. We reviewed 20 cases, 16 arising in the liver and 4 in the EHBD. Eighteen patients were women, with a mean age of 36.5 years. Eighteen tumors were multiloculated and 2 were unilocular. The tumor size ranged from 4 to 29 cm (average, 11 cm). The cyst fluid in 13 tumors was described as serous, in 2 as clear, in 2 others as hemorrhagic, and in 1 as serous and mucinous. Only in 2 tumors was the fluid described as mucinous. In 18 cystadenomas, the predominant epithelial lining consisted of a single layer of cuboidal or low-columnar nondysplastic cells similar to those of the gallbladder or bile ducts. This epithelial lining was strongly positive for cytokeratins 7 and 19, and focally positive for MUC1. Only 2 cystadenomas showed predominant intestinal differentiation characterized by mature goblet cells and columnar absorptive cells. These cells expressed CDX2, MUC2, and cytokeratin 20. Admixed with the goblet and columnar cells, there were serotonin-containing cells and Paneth cells. These 2 tumors showed extensive areas of high-grade dysplasia and invasive adenocarcinoma with intestinal phenotype. A subepithelial ovarian-like stroma was present in all tumors. None of the patients died of the tumors. We believe that the term mucinous cystic tumor recommended by the World Health Organization for all cystadenomas of the liver and EHBD is a misnomer.

An Algorithm for Creating Prognostic Systems for Cancer

The TNM staging system is universally used for classification of cancer. This system is limited since it uses only three factors (tumor size, extent of spread to lymph nodes, and status of distant metastasis) to generate stage groups. To provide a more accurate description of cancer and thus better patient care, additional factors or variables should be used to classify cancer. In this paper we propose a hierarchical clustering algorithm to develop prognostic systems that classify cancer according to multiple prognostic factors. This algorithm has many potential applications in augmenting the data currently obtained in a staging system by allowing more prognostic factors to be incorporated. The algorithm clusters combinations of prognostic factors that are formed using categories of factors. The dissimilarity between two combinations is determined by the area between two corresponding survival curves. Groups from cutting the dendrogram and survival curves of the individual groups define our prognostic systems that classify patients using survival outcomes. A demonstration of the proposed algorithm is given for patients with breast cancer from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.

An algorithm for expanding the TNM staging system

AIMnWe describe a new method to expand the tumor, lymph node, metastasis (TNM) staging system using a clustering algorithm. Cases of breast cancer were used for demonstration.nnnMATERIALS & METHODSnAn unsupervised ensemble-learning algorithm was used to create dendrograms. Cutting the dendrograms produced prognostic systems.nnnRESULTSnPrognostic systems contained groups of patients with similar outcomes. The prognostic systems based on tumor size and lymph node status recapitulated the general structure of the TNM for breast cancer. The prognostic systems based on tumor size, lymph node status, histologic grade and estrogen receptor status revealed a more detailed stratification of patients when grade and estrogen receptor status were added.nnnCONCLUSIONnPrognostic systems from cutting the dendrogram have the potential to improve and expand the TNM.

Association of urothelial carcinoma of the renal pelvis with papillary and medullary thyroid carcinomas. A new sporadic neoplastic syndrome

We describe 2 adult women (72 and 54 years), 1 with a low-grade noninvasive papillary urothelial carcinoma of the renal pelvis, who 14 years later developed a papillary carcinoma in 1 thyroid lobe and a medullary carcinoma in the contralateral lobe. Both neoplasms were similar in size and appeared symmetrical. Despite its small size, the medullary carcinoma metastasized in multiple cervical lymph nodes. The second patient had a high-grade invasive papillary urothelial carcinoma of the renal pelvis that infiltrated the renal parenchyma and metastasized in one of the lungs. Five months later, a papillary carcinoma was discovered in the thyroid gland. The 2 papillary thyroid carcinomas were of the follicular variant. Adjacent to 1 papillary carcinoma, there was a dominant nodule of a colloid and adenomatous goiter. The medullary carcinoma contained stromal amyloid and was immunoreactive for calcitonin and carcinoembryonic antigen. There was no C-cell hyperplasia (medullary carcinoma in situ). The 2 patients are alive, 1 is living with pulmonary metastasis from the high-grade urothelial carcinoma. Twelve cases of this neoplastic association were registered in the Survey, Epidemiology, and End Results Program from 1980 to 2009. We believe that the combination of these unusual neoplasms in the same patient may represent a new sporadic neoplastic syndrome.

Clustering big cancer data by effect sizes

We propose an effect size based approach to compute initial dissimilarities for Ensemble Algorithm of Clustering Cancer Data (EACCD). The proposed method is applied to the colon cancer data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute and compared with the log-rank approach where initial dissimilarities are computed from the log-rank test statistic. The experimental results show that under the proportional hazards assumption, the effect size approach generates robust results and has a better performance than the log-rank approach.

Analysis of Surveillance, Epidemiology, and End Results Database for Carcinoid Tumors

We read with great interest the article by Raz and colleagues 1 in CHEST (April 2015), in which the authors use public data from the Surveillance, Epidemiology, and End Results (SEER) program to demonstrate that individuals who undergo complete oncologic surgical resection of their typical carcinoid tumors have the best overall and disease-specifi c survival. In their analysis, the authors excluded a series of cohorts, such as cases with nodal positivity, distant metastases, prior cancers, and previous therapy, and maintained a signifi cant cohort of 4,111 cases for their fi nal dataset. Although the SEER database has some limitations, the size of the cohort under study provides for a variety of investigations not typically available to individual or collective researchers.

The anatomy of the TNM for colon cancer

BACKGROUNDnTo visualize the anatomy as revealed by dendrograms of the tumor, lymph node, and metastasis (TNM) staging system for colon cancer and compare it with the Dukes system.nnnMETHODSnA hierarchical clustering algorithm generated tree-structured dendrograms that stratified patients according to survival only. The dendrograms were constructed with the same prognostic variables used for the TNM. Because combinations of prognostic factors were stratified only on survival, additional factors of any number and type could be integrated into the TNM without changing the TNM categories.nnnRESULTSnThe algorithm provided a step-by-step visualization of the TNM and the Dukes system for colon cancer. Dendrograms and associated 5-year survival rates were generated for the T category only, the N category only, the T, N combination, and combinations of the T, N, and M, and the T, N, M with histological grade. Dendrograms revealed visual differences between the structure of TNM and the Dukes system of staging. Dendrograms also revealed how variations in prognostic factors changed survival. By cutting dendrograms along their dissimilarity axis, multiple prognostic subgroups could be created for colon cancer that may reflect outcomes that are more accurate to estimate.nnnCONCLUSIONSnDendrograms provide a new way to view cancer patient staging. They reveal a visual step-by-step hierarchical relationship between survival rates and combinations of prognostic variables. The dendrograms also revealed fundamental differences between the TNM and the Dukes system of staging. By stratifying on survival only, additional factors including molecular factors can be added to the TNM, because it classifies patients according to survival rates only and not according to pre-set rules of prognostic factors and stage groups. The clinical implications of stratifying only survival are discussed.

Effects of PSA screening guidelines on trends of diagnosis and treatment for prostate cancer: Analysis from the National Cancer Data Base (NCDB).

74 Background: The initial iteration of the USPSTF ‘Screening for Prostate Cancer’ guideline published in 2008 made recommendations against PSA screening for men > 75 years followed by an updated recommendation published in 2012 against PSA screening altogether. However, two large studies that formed the basis of these recommendations, the European ERSPC and the US-led PLCO trials, have published conflicting results. Currently, active surveillance is often offered as an approach to manage early stage prostate cancer. The NCDB was used to determine the uptake and efficacy of the USPSTF screening recommendations as well as their impact on the treatment of clinical T1c disease, which by definition, is cancer identified via screening to inform clinical practice. Methods: A de-identified dataset was acquired from NCDB. Frequencies were calculated for demographic variables; correlation coefficients and chi-square statistics were generated to assess any significant correlations between potential predictors (e.g....

Abstract P6-08-15: Deconstructing the TNM staging system for breast cancer

Background The TNM staging system is a standard classification for recording extent of disease in breast cancer. However, with progress in understanding tumor biology, it is unknown how new prognostic factors that will eventually be integrated with the TNM will affect its predictive ability. Our objective was to show the impact on 10-year survival rates for breast cancer as different combinations of prognostic factors are integrated into the TNM. Methods: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute for the years 1991 through 2000. After exclusions, 132,339 cases of female breast cancer were available. An ensemble clustering algorithm was used to calculate survival after including additional prognostic factors listed in SEER in the TNM. Combinations of the following 6 factors were sequentially added to the TNM: tumor grade, ER/PR status, age at diagnosis, racial/ethnic group, and histological tumor type. Results: Survival rates amongst some tumors with the same TNM stage varied as new factors were integrated into the TNM. Factors associated with favorable outcome usually were associated with better survival than factors associated with less favorable outcome for each stage group with varying degrees. There were 4 different tumor combinations that represented 4 different TNM stages that all corresponded to a 90% 10-year survival when additional factors were added to the TNM stage. Integration of additional prognostic factors led to a crossover in survival of some stage groups. In one combination (T1, N2, grade 1, ER+, PR+, age Conclusions: Integrating new prognostic factors into the TNM always changed the outcome. Survival rates, therefore, are relative and depend on the selection of prognostic factors. Adding new factors selected different cohorts from the population which had a heterogeneous population of cancer survivors. These cohorts usually had different survival rates compared with the overall population from which they were drawn. Integrating combinations of prognostic factors revealed frequent crossover of stage groups at 10 years, which is a violation of a staging system and could impact the interpretation of clinical trials. Citation Format: Jigar A Patel, Matthew T Hueman, Dechang Chen, Donald E Henson. Deconstructing the TNM staging system for breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-08-15.