Dedifferentiated Leiomyosarcoma-morphology, Immunohistochemistry, and Molecular Findings of a Case and Review of Literature.

We present a case of uterine dedifferentiated leiomyosarcoma in a 42-yr-old woman who presented with severe abdominal pain and vaginal bleeding. The mass measured 10.5 cm. The "differentiated" tumor component ranged from leiomyoma-like areas to smooth muscle tumor of uncertain malignant potential to frank leiomyosarcoma. The undifferentiated tumor component showed extreme hypercellularity, intermediate to large polygonal cells, with significant cytologic atypia and numerous mitotic figures (67 mitotic figures per 10 high-power fields). This undifferentiated component imperceptibly blended into more recognizable smooth muscle areas. In contrast to the differentiated component, the undifferentiated component lacked staining for smooth muscle markers. Targeted next-generation sequencing revealed TP53 , NF1 , and NOTCH2 mutations in both differentiated and undifferentiated components. In addition, the undifferentiated tumor component also harbored multiple additional chromosomal abnormalities including gains in 1q, 22q, and copy number losses in 3p, 9p, and 11q. The undifferentiated tumor component was also identified in an adhesion involving the small bowel and omentum at complete staging. The patient was subsequently treated with 6 cycles of adriamycin chemotherapy. Computerized tomography scan after 3 cycles showed no residual disease. Published literature regarding dedifferentiated leiomyosarcoma is reviewed.

Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes.

The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue. METHODS: In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform. RESULTS: The prediction model with SNV had an AUC of 1.00 (95% CI 1.00-1.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances. CONCLUSIONS: Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage.

Investigating the effect of optimal cytoreduction in the context of platinum sensitivity in high-grade serous ovarian cancer.

INTRODUCTION: The survival benefits of surgical cytoreduction in ovarian cancer are well-established. However, the surgical outcome has never been assessed while controlling for the efficacy of chemotherapy. This leaves the possibility that cytoreduction may not be beneficial for patients whose cancer does not respond well to adjuvant treatment. We sought to answer whether surgical cytoreduction independently improves overall survival when controlling for chemotherapy outcome. MATERIAL AND METHODS: We performed a retrospective case-control study using our institution's ovarian cancer database to evaluate the effect of optimal cytoreduction on advanced stage, high-grade serous ovarian cancer. Patients' characteristics were compared using both univariate and multivariate regression modeling to assess for independent predictors of overall survival. RESULTS: A total of 470 patients were assessed for inclusion; 234 responders to chemotherapy and 98 nonresponders. Significant survival characteristics were identified and included in the multivariate analysis. Independent predictors of survival in the multivariate analysis were age, responder status, optimal cytoreduction, neoadjuvant chemotherapy, and number of chemotherapy cycles. Kaplan-Meier survival curves showed improved survival for both patients who responded to chemotherapy and for those undergoing optimal cytoreduction (p < 0.001). We also demonstrated improved survival for patients receiving optimal cytoreduction among both nonresponders and responders (p < 0.001). CONCLUSIONS: Our analysis shows that patients who undergo optimal cytoreduction have an overall survival benefit regardless of their response to chemotherapy. Therefore, cytoreduction should be considered in all patients, even in those with advanced disease, if an optimal result can be achieved. This study was underpowered to assess patients who received neoadjuvant chemotherapy as a separate subgroup, but the order of treatment was controlled for in the overall analysis.

Integrated Clinical and Genomic Models to Predict Optimal Cytoreduction in High-Grade Serous Ovarian Cancer.

Advanced high-grade serous (HGSC) ovarian cancer is treated with either primary surgery followed by chemotherapy or neoadjuvant chemotherapy followed by interval surgery. The decision to proceed with surgery primarily or after chemotherapy is based on a surgeon's clinical assessment and prediction of an optimal outcome. Optimal and complete cytoreductive surgery are correlated with improved overall survival. This clinical assessment results in an optimal surgery approximately 70% of the time. We hypothesize that this prediction can be improved by using biological tumor data to predict optimal cytoreduction. With access to a large biobank of ovarian cancer tumors, we obtained genomic data on 83 patients encompassing gene expression, exon expression, long non-coding RNA, micro RNA, single nucleotide variants, copy number variation, DNA methylation, and fusion transcripts. We then used statistical learning methods (lasso regression) to integrate these data with pre-operative clinical information to create predictive models to discriminate which patient would have an optimal or complete cytoreductive outcome. These models were then validated within The Cancer Genome Atlas (TCGA) HGSC database and using machine learning methods (TensorFlow). Of the 124 models created and validated for optimal cytoreduction, 21 performed at least equal to, if not better than, our historical clinical rate of optimal debulking in advanced-stage HGSC as a control. Of the 89 models created to predict complete cytoreduction, 37 have the potential to outperform clinical decision-making. Prospective validation of these models could result in improving our ability to objectively predict which patients will undergo optimal cytoreduction and, therefore, improve our ovarian cancer outcomes.

Disparity of ovarian cancer survival between urban and rural settings.

OBJECTIVE: To determine if there is a difference in overall survival of patients with epithelial ovarian cancer in rural, urban, and metropolitan settings in the United States. METHODS: We performed a retrospective cohort study using 2004-2016 National Cancer Database (NCDB) data including high and low grade, stage I-IV disease. Bivariate analyses used Student's t-test for continuous variables and χ2 test for dichotomous variables. Kaplan-Meier curves estimated survival of patients based on location of residence, and univariate analyses using Cox proportional HR assessed survival based on baseline characteristics. Multivariate analysis was performed to account for significant covariates. Propensity score matching was used to validate the multivariate survival model. For all tests, p<0.05 was considered statistically significant. RESULTS: A total of 111 627 patients were included with a mean age of 62.5 years for metroolitan (range 18-90), 64.0 years for rural (range 19-90) and 63.2 years for urban areas (range 18-90). Of all patients included, 94 290 were in a metropolitan area (counties >1 million population or 50 000-999 999), 15 386 were in an urban area (population of 10 000-49 999), and 1951 were in a rural area (non-metropolitan/non-core population). Univariate Cox proportional hazards models showed clinically significant differences in survival in patients from metropolitan, urban, and rural areas. Multivariate Cox proportional hazards models showed a clinically significant increase in HRs for patients in rural settings (HR 1.17; 95% CI 1.06 to 1.29). Increasing age and stage, non-insured status, non-white race, and comorbidity were also significant for poorer survival. CONCLUSION: Patients with ovarian cancer who live in rural settings with small populations and greater distance to tertiary care centers have poorer survival. These differences hold after controlling for stage, age, and other significant risk factors related to poorer outcomes. To improve clinical outcomes, we need further studies to identify which of these factors are actionable.

A nuclear polymorphism at the 8q24 region is associated with improved survival time and chemo-response in high-grade serous ovarian cancer.

The 8q24 chromosomal region is strongly associated with an increased risk of ovarian cancer. One single nucleotide polymorphism that is associated with ovarian cancer in this region is rs6983267, located within the long non-coding RNA colon cancer associated transcript 2 (CCAT2). The aim of the present study was to assess the association between rs6983267 and clinical outcomes in patients with high-grade serous ovarian cancer (HGSOC). The present retrospective genetic association study utilized Sanger sequencing to determine the genotype at the rs6983267 locus (GG, GT, TT) in 98 patients with HGSOC. Survival time and chemotherapy responses between patients were compared with the TT genotype and patients with a genotype containing a G allele (GT, GG). Survival analyses were performed using Cox proportional hazard ratio analysis. Association with chemo-response was performed using a logistic regression. The results revealed that patients with HGSOC and the TT genotype at the rs6983267 locus had improved survival time compared with patients with genotypes containing a G allele [hazard ratio=0.59; 95% confidence interval (CI), 0.36-0.97; P=0.039] and were significantly associated with International Federation of Gynecology and Obstetrics stage [odds ratio (OR)=5.34; 95% CI, 1.50-22.62; P=0.014] and positive chemo-response (OR=4.51; 95% CI, 1.40-18.00; P=0.018). In summary, patients with HGSOC and the TT genotype at the rs6983267 locus had improved survival time compared with those with a G allele, despite being associated with more advanced disease; this was possibly due to an improved response to chemotherapy.

Identification of Novel lncRNAs in Ovarian Cancer and Their Impact on Overall Survival.

Long non-coding RNA's (lncRNA) are RNA sequences that do not encode proteins and are greater than 200 nucleotides in length. They regulate complex cellular mechanisms and have been associated with prognosis in various types of cancer. We aimed to identify lncRNA sequences that are associated with high grade serous ovarian cancer (HGSC) and assess their impact on overall survival. RNA was extracted from 112 HGSC patients and 12 normal fallopian tube samples from our Biobank tissue repository. RNA was sequenced and the Ultrafast and Comprehensive lncRNA detection and quantification pipeline (UClncR) was used for the identification of lncRNA sequences. Univariate logistic and multivariate lasso regression analyses identified lncRNA that was associated with HGSC. Univariate and multivariate Cox proportional hazard ratios were used to evaluate independent predictors of survival. 1943 of 16,325 investigated lncRNA's were differentially expressed in HGSC as compared to controls (p < 0.001). Nine of these demonstrated association with cancer after multivariate lasso regression. Our multivariate analysis of survival identified four lncRNA's associated with survival in HGSC. Three out of these four were found to be independently significant after accounting for all clinical covariates. Lastly, seven lncRNAs were independently associated with initial response to chemotherapy; four portended a worse response, while three were associated with improved response. More research is needed, but there is potential for these lncRNAs to be used as biomarkers of HGSC or predictors of treatment outcome in the future.

Clinical Impact of Local Progression in Pancreatic Cancer.

Background: The high prevalence of distant metastatic disease among patients with pancreatic cancer often draws attention away from the local pancreatic tumor. This study aimed to define the complications and hospitalizations from local versus distant disease progression among a retrospective cohort of patients with pancreatic cancer. Methods: Records of 298 cases of pancreatic cancer treated at a single institution from 2004 through 2015 were retrospectively reviewed, and cancer-related symptoms and complications requiring hospitalization were recorded. Hospitalizations related to pancreatic cancer were attributed to either local or distant progression. Cumulative incidence analyses were used to estimate the incidence of hospitalization, and multivariable Fine-Gray regression models were used to identify factors predictive of hospitalizations. Results: The 1-year cumulative incidences of hospitalization due to local versus distant disease progression were 31% and 24%, respectively. Among 509 recorded hospitalizations, leading local etiologies included cholangitis (10%), biliary obstruction (7%), local procedure complication (7%), and gastrointestinal bleeding (7%). On multivariable analysis, significant predictors of hospitalization from local progression included unresectable disease (subdistribution hazard ratio [SDHR], 2.42; P<.01), black race (SDHR, 3.34; P<.01), younger age (SDHR, 1.02 per year; P=.01), tumor in the pancreatic head (SDHR, 2.19; P<.01), and larger tumor size (SDHR, 1.13 per centimeter; P=.02). Most patients who died in the hospital from pancreatic cancer (56%) were admitted for complications of local disease progression. Conclusions: Patients with pancreatic cancer experience significant complications of local tumor progression. Although distant metastatic progression represents a hallmark of pancreatic cancer, future research should also focus on improving local therapies.

A divalent interaction between HPS1 and HPS4 is required for the formation of the biogenesis of lysosome-related organelle complex-3 (BLOC-3).

Hermansky-Pudlak syndrome (HPS) is a group of rare autosomal recessive disorders characterized by oculocutaneous albinism, a bleeding tendency, and sporadic pulmonary fibrosis, granulomatous colitis or infections. Nine HPS-causing genes have been identified in humans. HPS-1 is the most severe subtype with a prevalence of ~1/1800 in northwest Puerto Rico due to a founder mutation in the HPS1 gene. Mutations in HPS genes affect the biogenesis of lysosome-related organelles such as melanosomes in melanocytes and platelet dense granules. Two of these genes (HPS1 and HPS4) encode the HPS1 and HPS4 proteins, which assemble to form a complex known as Biogenesis of Lysosome-related Organelle Complex 3 (BLOC-3). We report the identification of the interacting regions in HPS1 and HPS4 required for the formation of this complex. Two regions in HPS1, spanning amino acids 1-249 and 506-700 are required for binding to HPS4; the middle portion of HPS1 (residues 250-505) is not required for this interaction. Further interaction studies showed that the N-termini of HPS1 and HPS4 interact with each other and that a discrete region of HPS4 (residues 340-528) interacts with both the N- and C-termini of the HPS1 protein. Several missense mutations found in HPS-1 patients did not affect interaction with HPS4, but some mutations involving regions interacting with HPS4 caused instability of HPS1. These observations extend our understanding of BLOC-3 assembly and represent an important first step in the identification of domains responsible for the biogenesis of lysosome-related organelles.

Clinical, molecular, and cellular features of non-Puerto Rican Hermansky-Pudlak syndrome patients of Hispanic descent.

Hermansky-Pudlak syndrome (HPS) is an autosomal recessive condition characterized by a bleeding diathesis and hypopigmentation of the skin, hair, and eyes. Some HPS patients develop other complications such as granulomatous colitis and/or fatal pulmonary fibrosis. Eight genes have been associated with this condition, resulting in subtypes HPS-1 through HPS-8. The HPS gene products are involved in the biogenesis of specialized lysosome-related organelles such as melanosomes and platelet delta granules. HPS1 and HPS4 form a stable complex named biogenesis of lysosome-related organelles complex (BLOC)-3, and patients with BLOC-3 or AP-3 deficiency develop pulmonary fibrosis. Therefore, it is important to subtype each HPS patient. HPS type 1 (HPS-1) occurs frequently on the island of Puerto Rico because of a founder mutation. Here, we describe seven mutations, six of which, to our knowledge, are previously unreported in the HPS1, HPS4, and HPS5 genes among patients of Mexican, Uruguayan, Honduran, Cuban, Venezuelan, and Salvadoran ancestries. Our findings demonstrate that the diagnosis of HPS should be considered in Hispanic patients with oculocutaneous albinism and bleeding symptoms. Moreover, such patients should not be assumed to have the HPS-1 subtype typical of northwest Puerto Rican patients. We recommend molecular HPS subtyping in such cases, as it may have significant implications for prognosis and intervention.

A BLOC-1 mutation screen reveals that PLDN is mutated in Hermansky-Pudlak Syndrome type 9.

Hermansky-Pudlak Syndrome (HPS) is an autosomal-recessive condition characterized by oculocutaneous albinism and a bleeding diathesis due to absent platelet delta granules. HPS is a genetically heterogeneous disorder of intracellular vesicle biogenesis. We first screened all our patients with HPS-like symptoms for mutations in the genes responsible for HPS-1 through HPS-6 and found no functional mutations in 38 individuals. We then examined all eight genes encoding the biogenesis of lysosome-related organelles complex-1, or BLOC-1, proteins in these individuals. This identified a homozygous nonsense mutation in PLDN in a boy with characteristic features of HPS. PLDN is mutated in the HPS mouse model pallid and encodes the protein pallidin, which interacts with the early endosomal t-SNARE syntaxin-13. We could not detect any full-length pallidin in our patient's cells despite normal mRNA expression of the mutant transcript. We could detect an alternative transcript that would skip the exon that harbored the mutation, but we demonstrate that if this transcript is translated into protein, although it correctly localizes to early endosomes, it does not interact with syntaxin-13. In our patient's melanocytes, the melanogenic protein TYRP1 showed aberrant localization, an increase in plasma-membrane trafficking, and a failure to reach melanosomes, explaining the boy's severe albinism and establishing his diagnosis as HPS-9.