Metastatic squamous cell carcinoma to the colon arising from a mature cystic ovarian teratoma

Malignant transformation of a mature cystic teratoma is extremely rare, occurring in 0.17-2% of cases.1 The most common malignant degeneration is squamous cell carcinoma (SCC) arising from the ectoderm. Approximately half of all cases of SCC of the ovary are confined to the ovary at time diagnosis.1,2 Secondary to its absolute rarity and the relative infrequency of cases with metastatic spread the optimal treatment of advanced stage disease is unknown. Outcomes for locally advanced and widespread disease have historically been very poor. Ford and Timmons recently reported on a patient with stage IIC SCC arising in a mature cystic teratoma treated with multimodal therapy who has been free of disease for more than five years.3 Herein we report on a woman with stage IIIC SCC arising within a mature cystic teratoma treated with directed chemoradiation who subsequently developed metastatic SCC to the colon

Pancreatic Cysts Identification Using Unstructured Information Management Architecture

poster abstractPancreatic cancer is one of the deadliest cancers, mostly diagnosed at late stages. Patients with pancreatic cysts are at higher risk of developing cancer and surveillance of these patients can help with early diagnosis. Much information about pancreatic cysts can be found in free text format in various medical narratives. In this retrospective study, a corpus of 1064 records from 44 patients at Indiana University Hospital from 1990 to 2012 was collected. A natural language processing system was developed and used to identify patients with pancreatic cysts. The input goes through series of tasks within the Unstructured Information Management Architecture (UIMA) framework consisting of report separation, metadata detection, sentence detection, concept annotation and writing into the database. Metadata such as medical record number (MRN), report id, report name, report date, report body were extracted from each report. Sentences were detected and concepts within each sentence were extracted using regular expression. Regular expression is a pattern of characters matching specific string of text. Our medical team assembled concepts that are used to identify pancreatic cysts in medical reports and additional keywords were added by searching through literature and Unified Medical Language System (UMLS) knowledge base. The Negex Algorithm was used to find out negation status of concepts. The 1064 reports were divided into sets of train and test sets. Two pancreatic-cyst surgeons created the gold standard data (Inter annotator agreement K=88%). The training set was analyzed to modify the regular expression. The concept identification using the NegEx algorithm resulted in precision and recall of 98.9% and 89% respectively. In order to improve the performance of negation detection, Stanford Dependency parser (SDP) was used. SDP finds out how words are related to each other in a sentence. SDP based negation algorithm improved the recall to 95.7%

A phase II study of paclitaxel for the treatment of ovarian stromal tumors: An NRG Oncology/ Gynecologic Oncology Group Study

To estimate the probability of complete clinical response and toxicity of paclitaxel as second-line chemotherapy in measurable disease patients with malignant tumors of the ovarian stroma, and to evaluate the value of inhibin for predicting response

Disease Extent at Secondary Cytoreductive Surgery is Predictive of Progression-free and Overall Survival in Advanced Stage Ovarian Cancer: an NRG Oncology/Gynecologic Oncology Group study

Purpose GOG 152 was a randomized trial of secondary cytoreductive surgery (SCS) in patients with suboptimal residual disease (residual tumor nodule >1 cm in greatest diameter) following primary cytoreductive surgery for advanced stage ovarian cancer. The current analysis was undertaken to evaluate the impact of disease findings at SCS on progression-free survival (PFS) and overall survival (OS). Methods Among the 550 patients enrolled on GOG-152, two-hundred-sixteen patients were randomly assigned following 3 cycles of cisplatin and paclitaxel to receive SCS. In 15 patients (7%) surgery was declined or contraindicated. In the remaining 201 patients the operative and pathology reports were utilized to classify their disease status at the beginning of SCS as; no gross disease/microscopically negative N= 40 (19.9%), no gross disease/microscopically positive N= 8 (4.0%), and gross disease N=153 (76.1%). Results The median PFS for patients with no gross disease/microscopically negative was 16.1 months, no gross disease/microscopically positive was 13.5 months and for gross disease was 11.7 months, p=0.002. The median OS for patients with no gross disease/microscopically negative was 51.5 months, no gross disease/microscopically positive was 42.6 months and for gross disease was 34.9 months, p=0.018. Conclusion Although as previously reported SCS did not change PFS or OS, for those who underwent the procedure, their operative and pathologic findings were predictive of PFS and OS. Surgical/pathological residual disease is a biomarker of response to chemotherapy and predictive of PFS and OS

Genome-wide association study evaluating single-nucleotide polymorphisms and outcomes in patients with advanced stage serous ovarian or primary peritoneal cancer: An NRG Oncology/Gynecologic Oncology Group study

This study evaluated single nucleotide polymorphisms (SNPs) associated with progression free (PFS) and overall survival (OS) in patients with advanced stage serous EOC

Gene Expression Profiles in Stage I Uterine Serous Carcinoma in Comparison to Grade 3 and Grade 1 Stage I Endometrioid Adenocarcinoma

Endometrial cancer is the most common gynecologic malignancy in the developed countries. Clinical studies have shown that early stage uterine serous carcinoma (USC) has outcomes similar to early stage high grade endometrioid adenocarcinoma (EAC-G3) than to early stage low grade endometrioid adenocarcinoma (EAC-G1). However, little is known about the origin of these different clinical outcomes. This study applied the whole genome expression profiling to explore the expression difference of stage I USC (n = 11) relative to stage I EAC-G3 (n = 11) and stage I EAC-G1 (n = 11), respectively.We found that the expression difference between USC and EAC-G3, as measured by the number of differentially expressed genes (DEGs), is consistently less than that found between USC and EAC-G1. Pathway enrichment analyses suggested that DEGs specific to USC vs. EAC-G3 are enriched for genes involved in signaling transduction, while DEGs specific to USC vs. EAC-G1 are enriched for genes involved in cell cycle. Gene expression differences for selected DEGs are confirmed by quantitative RT-PCR with a high validation rate.This data, although preliminary, indicates that stage I USC is genetically similar to stage I EAC-G3 compared to stage I EAC-G1. DEGs identified from this study might provide an insight in to the potential mechanisms that influence the clinical outcome differences between endometrial cancer subtypes. They might also have potential prognostic and therapeutic impacts on patients diagnosed with uterine cancer

Microarray Analysis Reveals Distinct Gene Expression Profiles Among Different Tumor Histology, Stage and Disease Outcomes in Endometrial Adenocarcinoma

Endometrial cancer is the most common gynecologic malignancy in developed countries and little is known about the underlying mechanism of stage and disease outcomes. The goal of this study was to identify differentially expressed genes (DEG) between late vs. early stage endometrioid adenocarcinoma (EAC) and uterine serous carcinoma (USC), as well as between disease outcomes in each of the two histological subtypes.Gene expression profiles of 20 cancer samples were analyzed (EAC = 10, USC = 10) using the human genome wide illumina bead microarrays. There was little overlap in the DEG sets between late vs. early stages in EAC and USC, and there was an insignificant overlap in DEG sets between good and poor prognosis in EAC and USC. Remarkably, there was no overlap between the stage-derived DEGs and the prognosis-derived DEGs for each of the two histological subtypes. Further functional annotation of differentially expressed genes showed that the composition of enriched function terms were different among different DEG sets. Gene expression differences for selected genes of various stages and outcomes were confirmed by qRT-PCR with a high validation rate.This data, although preliminary, suggests that there might be involvement of distinct groups of genes in tumor progression (late vs. early stage) in each of the EAC and USC. It also suggests that these genes are different from those involved in tumor outcome (good vs. poor prognosis). These involved genes, once clinically verified, may be important for predicting tumor progression and tumor outcome