Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy

BACKGROUND

A gene expression profile (GEP) test able to accurately identify risk of metastasis for patients with cutaneous melanoma has been clinically validated.

OBJECTIVE

We aimed for assessment of the prognostic accuracy of GEP and sentinel lymph node biopsy (SLNB) tests, independently and in combination, in a multicenter cohort of 217 patients.

METHODS

Reverse transcription polymerase chain reaction (RT-PCR) was performed to assess the expression of 31 genes from primary melanoma tumors, and SLNB outcome was determined from clinical data. Prognostic accuracy of each test was determined using Kaplan-Meier and Cox regression analysis of disease-free, distant metastasis-free, and overall survivals.

RESULTS

GEP outcome was a more significant and better predictor of each end point in univariate and multivariate regression analysis, compared with SLNB (P < .0001 for all). In combination with SLNB, GEP improved prognostication. For patients with a GEP high-risk outcome and a negative SLNB result, Kaplan-Meier 5-year disease-free, distant metastasis-free, and overall survivals were 35%, 49%, and 54%, respectively.

LIMITATIONS

Within the SLNB-negative cohort of patients, overall risk of metastatic events was higher (∼30%) than commonly found in the general population of patients with melanoma.

CONCLUSIONS

In this study cohort, GEP was an objective tool that accurately predicted metastatic risk in SLNB-eligible patients.

Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma

PURPOSE

The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis.

EXPERIMENTAL DESIGN

A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis.

RESULTS

RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC = 0.93) and validation (ROC = 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis.

CONCLUSIONS

The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented.

Causal factors of hot air ballooning incidents: identification, frequency, and potential impact

BACKGROUND

Hot air ballooning incidents are relatively rare; however, when they do occur they are likely to result in a fatality or serious injury. Human error is commonly attributed as the cause of hot air ballooning incidents; however, error in itself is not an explanation for safety failures. This research aims to identify and establish the relative importance of factors contributing toward hot air ballooning incidents.

METHODS

Twenty-two Australian Ballooning Federation (ABF) incident reports were thematically coded using a bottom-up approach to identify causal factors. Subsequently, 69 balloonists (mean 19.51 yr experience) participated in a survey to identify additional causal factors and rate (out of 7) the perceived frequency and potential impact to ballooning operations of each of the previously identified causal factors. Perceived associated risk was calculated by multiplying mean perceived frequency and impact ratings.

RESULTS

Incident report coding identified 54 causal factors within 9 higher level areas: Attributes, Crew Resource Management, Equipment, Errors, Instructors, Organizational, Physical Environment, Regulatory Body, and Violations. Overall, 'weather', 'inexperience,' and 'poor/inappropriate decisions' were rated as having greatest perceived associated risk.

DISCUSSION

Although errors were nominated as a prominent cause of hot air ballooning incidents, physical environment and personal attributes are also particularly important for safe hot air ballooning operations. In identifying a range of causal factors, the areas of weakness surrounding ballooning operations have been defined; it is hoped that targeted safety and training strategies can now be put into place to remove these contributing factors and reduce the chance of pilot error.

Current clinical practice: differential management of uveal melanoma in the era of molecular tumor analyses

Objective

Assess current clinical practices for uveal melanoma (UM) and the impact of molecular prognostic testing on treatment decisions.

Design

Cross-sectional survey and sequential medical records review.

Participants

Ophthalmologists who treat UM.

Methods

(A) Medical records review of all Medicare beneficiaries tested by UM gene expression profile in 2012, conducted under an institutional review board-approved protocol. (B) 109 ophthalmologists specializing in the treatment of UM were invited to participate in 24-question survey in 2012; 72 were invited to participate in a 23-question survey in 2014.

Main outcome measures

Responses analyzed by descriptive statistics, frequency analyses (percentages, Tukey, histograms), and Fisher’s exact test. Descriptive presentation of essay answers.

Results

The review of Medicare medical records included 191 evaluable patients, 88 (46%) with documented medical treatment actions or institutional policies related to surveillance plans. Of these 88, all gene expression profiling (GEP) Class 1 UM patients were treated with low-intensity surveillance. All GEP Class 2 UM patients were treated with high-intensity surveillance (P<0.0001 versus Class 1). There were 36 (19%) with information concerning referrals after initial diagnosis. Of these 36, all 23 Class 2 patients were referred to medical oncology; however, none of the 13 Class 1 patients were referred (P<0.0001 versus Class 1). Only Class 2 patients were recommended for adjunctive treatment regimens. 2012 survey: 50 respondents with an annual median of 35 new UM patients. The majority of respondents (82%) performed molecular analysis of UM tumors after fine needle biopsy (FNAB); median: 15 FNAB per year; 2014 survey: 35 respondents with an annual median of 30 new UM patients. The majority offered molecular analyses of UM tumor samples to most patients. Patients with low metastatic risk (disomy 3 or GEP Class 1) were generally assigned to less frequent (every 6 or 12 months) and less intensive clinical visits. Patients with high metastatic risk (monosomy 3 or GEP Class 2) were assigned to more frequent surveillance with hepatic imaging and liver function testing every 3–6 months. High-risk patients were considered more suitable for adjuvant treatment protocols.

Conclusion

The majority of ophthalmologists treating UM have adopted molecular diagnostic tests for the purpose of designing risk-appropriate treatment strategies.

A proprietary multianalyte test for predicting extreme resistance to neoadjuvant 5-FU based chemoradiation (CTRT) in esophageal adenocarcinoma (EC)

51

Background: Standard of care for localized EC is neoadjuvant CTRT followed by surgery. Although 5-FU based regimens are still commonly used, other regimens (CROSS) are also prescribed. Published EC studies report 20-25% of patients exhibit extreme resistance (exCTRT) to 5-FU based neoadjuvant treatment (NT); these patients may benefit from alternative treatment regimens. We have developed a proprietary assay using a training set of 167 patients to accurately identify patients with exCTRT (ROC 0.96). The results presented herein constitute an independent clinical validation. Methods: Biopsy samples from 71 pts diagnosed to have EC and who had undergone surgical excision following NT were obtained. IHC detection of NF-kB, SHH, and Gli-1 proteins in FFPE sections was performed in a CLIA approved lab. A GI pathologist and an expert clinical scientist blindly evaluated resection specimens and assigned a labeling index (LI) score. The LI for each case was compared to the established training set and the predicted response determined using a logistic regression algorithm. Blinded pathology scoring for exCTRT vs. non-exCTRT was performed for all samples using both CAP Tumor Response Grade (TRG) and the Rohatgi research scale. Results: Of the 71 EC cases in the clinical validation cohort, 24 had an outcome of exCTRT (<50% reduction in tumor following neoadjuvant treatment; TRG 3) and 47 had an outcome of non-exCTRT (>50% reduction in tumor; TRG 0-2). ROC for the validation cohort was 0.85. The positive predictive value for the validation study was 83%, reflecting an assay that can accurately predict those likely to have some degree of response to chemotherapy / radiation. Conversely, a negative predictive value of 83% with specificity of 94% was achieved indicating accurate identification of those not likely to benefit from neoadjuvant treatment. Conclusions: The analysis of NF-kB, SHH, and Gli-1 in EC tissue can accurately identify patients unlikely to respond to 5-FU based NT. These results are now confirmed using a CLIA accredited lab and a multicenter independent validation cohort of esophageal adenocarcinoma biopsies.

A gene signature to determine metastatic behavior in thymomas

Purpose

Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.

Methods

qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75).

Results

A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036).

Conclusion

A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.

Gene expression profile of primary cutaneous melanomas to distinguish between low and high risk of metastasis

9022

Background: Wide variability exists in metastatic rates of primary cutaneous melanoma (CM), even within TNM stage groupings. We developed an RT-PCR based gene expression profile (GEP) test to predict distant metastases in early stage CM. Methods: RNA was isolated from formalin-fixed, paraffin embedded biopsies or wide excisions of primary CM from patients with stage 1-4 CM (87% stage 1-2) converted to cDNA and analyzed using RT-PCR. All analyses were done using JMP Genomics and WinSTAT. Radial Basis Machine (RBM) modeling was used to predict metastasis-free survival (MFS) for the training set of 149 samples. Independent validation was performed on an additional 107 CM samples. RBM reports a binary Class 1 (low risk) and Class 2 (high risk). Results: Analysis of the training set resulted in a model with 85% receiver operating characteristic (ROC) and sensitivity of 82%. Prediction of metastatic risk for the validation set resulted in a 90% ROC and sensitivity of 89%. 30 of 33 stage 1-3 cases with a known metastatic event were accurately called Class 2. Kaplan-Meier analysis showed 5-year MFS rates of 88% and 25% for predicted Class 1 and Class 2, respectively, in the training set (p<0.0001, overall MFS=60%). Similarly, MFS was 95% and 26% for Class 1 and Class 2, respectively, in the independent validation set (p<0.0001, overall MFS=67%). Univariate Cox regression analysis of the validation set revealed that GEP, AJCC stage, Breslow thickness, and ulceration were each predictors of metastatic risk (HR=27.2, 11.4, 3.0, and 11.6, respectively, p<0.002 for each). Multivariate analysis showed GEP and AJCC stage were independent predictors of risk (HR=8.4 and 6.4 respectively, p<0.007 for both). Conclusions: This GEP signature provides an accurate stratification of metastatic risk in the training and validation samples independent of all other histologic factors. This test may serve as a prognostic tool for outcomes in patients with melanoma and for stratifying patients for clinical trials.

A gene signature to determine metastatic behavior in thymic carcinoma

7605

Background: Thymomas and thymic carcinomas (TC) are rare epithelial tumors derived from the thymic gland in the anterior mediastinum. Although all histological types of thymomas, albeit with different frequencies, can give rise to metastases, TC have a more aggressive behavior and metastasize earlier and more frequently than thymomas. We previously developed a prognostic gene signature able to accurately determine metastatic behavior of thymomas (Gökmen-Polar et al. ASCO 2012). The signature is currently used in clinical practice to identify patients at high or low risk for metastatic disease. In the current study, we sought to evaluate the utility of this signature for determining risk from TC tumors. Methods: FFPE tissue sections were macrodissected from 35 primary TC. RNA was isolated and RT-PCR was performed to assess the expression of 23 genes (19 test and four reference genes). Predictive modeling was performed using Radial Basis Machine (RBM) software from JMP Genomics (SAS), and survival analysis was done using the Kaplan-Meier method. Results: Samples from the TC cohort ranged from stage II through IVB, with a median age of 54 years. 26 samples had evidence of metastatic progression, while nine samples did not. Prediction of metastasis, based upon comparison to the previously developed thymoma training set and using a 19-gene signature, yielded an ROC = 0.66. Independent analysis of the TC cohort with the thymoma 19-gene signature resulted in a predictive model with an ROC = 0.97 (overall accuracy = 87%, sensitivity = 73% and specificity=100%). Further modeling and gene set reduction revealed a separate ten-gene signature able to segregate metastatic from non-metastatic cases with 100% accuracy. All the cases classified as high risk (n= 26) developed metastasis within 5 years while none of the cases categorized as low-risk (n= 9) had any events at 5 years of follow-up. Conclusions: A ten-gene signature was established that appears to predict metastatic behavior of TC with a high degree of accuracy; however, validation in an independent cohort is necessary. Our data suggests that the biologic determinants of the clinical course of TC maybe distinct from thymoma and could be used to improve patient management.

A 19-gene prognostic GEP signature to determine metastatic risk associated with thymomas

68

Background: Therapeutic decisions for patients with thymomas are made on tumor stage as histologic classification is of limited prognostic value. A molecular prognostic tool may better predict the likelihood of metastasis in thymomas and enable better management of patients. Methods: Reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay for 23 genes (19 test and 4 reference genes) was performed on archival paraffin-embedded primary thymomas (n=36). The gene expression levels were used to compute gene expression profile (GEP) signature and classify tumors into low or high risk. The GEP was validated in an independent test set (n=75) of patients. Results: We developed and validated a 19-gene prognostic GEP signature for predicting metastatic behavior in thymomas. Using radial basis machine (RBM) modeling in the training set, both 5-year and 10-year MFS rates were 85% and 22% for predicted low risk and high risk of metastasis (p<0.0005, log-rank), respectively. For the validation set, 5-year MFS rates were 93% and 35% for predicted low and high risk patients (p<0.0018 log-rank), respectively. The 5-year MFS rates for Masaoka stage in the validation set were 53% and 41% for stage I/II and stage III/IV(p<0.0433 log-rank), respectively. In a multivariate Cox model, the GEP was the only independent predictor of metastasis free survival compared to age at diagnosis and stage (p=0.048). Conclusions: Using archival tissues, we identified and validated a 19-gene signature that predicts likelihood of metastases of thymomas more accurately than traditional staging. The signature provides insights for both patient stratification and targeted therapy.

BMP-specific SMADs function as novel repressors of PDGFA and modulate its expression in ovarian granulosa cells and tumors

Platelet-derived growth factor alpha (PDGFA) is frequently upregulated in various cancers and thought to function as a key player in the development and progression of tumor growth by regulating aspects of cell proliferation, angiogenesis and metastasis. However, the mechanism by which it is upregulated is not fully understood. Previously, we demonstrated that conditional deletion of two transcription factors that signal for the bone morphogenetic proteins (Smad1 and Smad5) in ovarian granulosa cells causes metastatic granulosa cell tumors (GCTs) in female mice and phenocopies human juvenile GCTs (JGCTs). Smad1/5 double conditional knockout tumors, as well as human JGCTs, are highly vascularized, hemorrhagic and mitotically active. Expression analysis of these tumors and their metastases revealed a significant upregulation of key proliferation and pro-angiogenic factors such as Pdgfa, Pdgfb and Vegf. We examined whether these genes were direct targets of SMAD1 and SMAD5. Knockdown of SMAD1 and SMAD5 in mouse primary granulosa cells and a human GCT-derived cell line (COV434) resulted in upregulation of PDGFA, but not PDGFB nor VEGF. We identified several putative SMAD1/5-binding sites in the PDGFA promoter, and chromatin immunoprecipitation and reporter assays demonstrated that SMAD1/5 interact with the PDGFA promoter to regulate its activity. Further, SMAD1/5 antagonize the activity of the transcription factor Sp1, a well-known positive regulator of PDGFA, by inhibiting its occupancy at a key regulatory site on the proximal PDGFA promoter. Collectively, our studies establish that loss of SMAD1/5 leads to upregulation of PDGFA in ovarian granulosa cells, and that a novel regulatory interaction exists between the BR-SMADs and Sp1 in controlling PDGFA expression during granulosa cell tumorigenesis.

A 19-gene prognostic GEP signature (DecisionDx-Thymoma) to determine metastatic risk associated with thymomas

7106

Background: The treatment of thymomas is predominantly based on the stage of disease. Histologic classification is of limited value as all types of thymomas can give rise to metastases. In order to better predict the metastatic behavior of these tumors, we performed genome-wide gene expression analysis and identified a set of genes associated with presence or absence of metastases. In the current study, we sought to further develop and validate the gene signature using quantitative RT-PCR analysis. Methods: Thymomas with archived blocks and long-term follow-up data were reviewed. This training set study consisted of 50 cases, including 34 cases on which the discovery microarray analysis had been performed. RNA was extracted from 5 x 10-micron thick sections in a CAP-accredited CLIA certified laboratory and analyzed by RT-PCR using custom TLDA cards on an ABI7900HT instrument. Expression data and biostatistical analysis were performed using GeNorm and JMP Genomics (SAS). Predictive modeling using Partition Tree Analysis (PTA) and Logistic Regression Analysis (LRA) was performed. Metastasis-free survival (MFS) was assessed using Kaplan-Meier analysis. Results: A 19-gene expression profile (GEP) signature was developed using a cohort of 50 thymomas for predicting metastasis. PTA yielded ROC of 0.97 (met. accuracy = 96%, non-met. accuracy = 81%), while LRA yielded ROC of 0.895 (met. accuracy = 87%, non-met. accuracy = 85%). PTA classification showed 5-year MFS rates of 100% and 31% for predicted low risk (Class 1) and high risk (Class 2) of metastasis (median MFS = NR and 4.1 yrs, resp., P<0.0001 Log-Rank), respectively. LRA showed 5-year MFS rates of 100% and 17% for predicted Class 1 and high risk Class 2 of metastasis (median MFS = NR and 2.9 yrs, resp., P<0.0001 Log-Rank), respectively. Analysis of additional cohorts is ongoing. Conclusions: We have successfully completed development of a 19-gene signature (DecisionDx-Thymoma) that appears to predict metastatic behavior of thymomas more accurately than traditional staging. If validated in larger cohort, this signature will provide insight for the future management of patients with this rare malignancy.

Gene expression profile signature (DecisionDx-Melanoma) to predict visceral metastatic risk in patients with stage I and stage II cutaneous melanoma

8543

Background: The current AJCC TNM staging system has poor specificity for predicting visceral metastatic risk in patients diagnosed with stage I or stage II cutaneous melanoma. We, therefore, developed a gene expression profile signature (GEP) following in silico investigation of previously published microarray analyses. Methods: 60 formalin fixed paraffin embedded primary cutaneous melanoma samples from patients with stage I or II cutaneous melanoma with at least a follow up period of at least 6 years were macrodissected and analyzed blindly. RNA was isolated, converted to cDNA and RT-PCR was performed to assess the expression of the gene set. Expression data and biostatistical analysis was performed using GeNorm and JMP Genomics (SAS) Predictive modeling included Radial Basis Machine (RBM) and Partition Tree Analysis (PTA) Metastasis-free survival (MFS) was assessed using Kaplan-Meier analysis. The following clinical data was retrieved from medical records: survival, metastases, types of metastases. 20 out of 60 patients had developed visceral metastases in the follow up period. Results: GEP was developed following multiple analytical approaches.Two types of signatures emerged: Low risk (Class 1) and High risk (Class 2). Without optimizing for sensitivity, the analyses of the 60 sample cohort by radial basis machine (RBM) resulted in 92% ROC (met. accuracy = 90%, non-met. accuracy = 85%), while partition tree analysis (PTA) yielded 99% ROC (met. accuracy = 100%, non-met. accuracy = 95%). RBM classification showed 6-year MFS rates of 97% for Class 1 and 19% for predicted Class 2 of metastasis (median MFS = NR and 5.6 yrs, resp., P<0.0001 Log-Rank respectively). PTA showed 6-year MFS rates of 100% for predicted Class 1 and 14% for Class 2 of metastasis (median MFS = NR and 5.4 yrs, resp., P<0.0001 Log-Rank respectively). Conclusions: This study shows that DecisionDx-Melanoma GEP signature can provide excellent accuracy in predicting metastatic risk in stage I and II cutaneous melanoma.To our knowledge, the GEP provides the most accurate predictor to date for development of visceral metastases in patients with Stage I and II cutaneous melanoma.

Detection of biomarkers for esophageal cancer pathologic complete response (pathCR) in OE33 and NCI-H460 control cell lines using a clinical standard operating procedure (SOP) protocol

20

Background: The standard of care for esophageal cancer (EC) patients is a trimodality approach that includes chemo− and radiotherapy followed by surgery. Approximately 25% of EC patients exhibit pathCR to chemoradiotherapy, but undergo unnecessary surgical resection procedures. A set of three protein biomarkers (NF−kB, SHH, and Gli−1) able to effectively identify pathCR status from diagnostic patient biopsies was discovered at M. D. Anderson Cancer Center (uncorrected ROC=0.97; corrected ROC=0.96). To translate that discovery to the clinical laboratory, a standardized protocol utilizing clinical grade reagents and instrumentation for biomarker detection has been developed. PathCR determination with this clinical procedure would be a significant step toward individualized therapeutic options for EC patients.

Methods: OE33 and NCI−H460 cells were grown to confluence, collected, and fixed with PFA as a cell pellet. Fixed cell pellets were paraffin embedded, sectioned, and adhered to microscope slides. IHC detection of NF−kB, SHH, and Gli-1 proteins was performed in each cell line using clinical grade reagents and instrumentation, and protein localization was determined by microscopy to verify concordance with research laboratory techniques and results.

Results: The clinical SOP allowed for efficient staining of each pathCR biomarker. Nuclear localization of activated NF-kB and Gli-1 was observed in OE33 and NCI-H460 cells, respectively, and SHH localization to the cytoplasm of NCI-H460 cells was also confirmed. The results correlate well with staining protocols utilized during research laboratory procedures.

Conclusions: The clinical SOP for IHC detection of EC pathCR biomarkers can efficiently detect NF-kB, SHH, and Gli−1 in the control cell lines OE33 and NCI-H460. The protocols presented should be adaptable to EC patient tumor biopsies, providing an effective method for determining pathCR that will facilitate an individualized approach to treatment methods for people suffering from EC.

Silent pituitary corticotroph carcinoma in a young dog

An 11-month-old neutered female weimaraner was humanely destroyed 6 days after an acute onset of neurological signs. At necropsy examination the pituitary gland was replaced by a large neoplastic mass that compressed and infiltrated the overlying hypothalamus. Small nodules were detected in the spleen, kidneys and stomach. Adrenal, thyroid and parathyroid glands were normal in size. The primary pituitary mass, visceral nodules and microscopical metastases detected within the ventricles and leptomeninges of the brain comprised polygonal, chromophobic neoplastic cells, which labelled strongly for adrenocorticotrophic hormone (ACTH) on immunohistochemical examination. These findings, in the absence of clinical or pathological evidence of pituitary-dependent hyperadrenocorticism, support a diagnosis of endocrinologically-inactive ('silent') pituitary corticotroph (ACTH-containing) carcinoma.

Mapping cerebellar abiotrophy in Australian Kelpies

An autosomal recessive form of cerebellar abiotrophy occurs in Australian Kelpie dogs. Clinical signs range from mild ataxia with intention tremor to severe ataxia with seizures. A whole-genome mapping analysis was performed using Affymetrix Canine SNP array v2 on 11 affected and 19 control dogs, but there was no significant association with disease. A homozygosity analysis identified a three megabase region likely to contain the disease mutation. The region spans 29.8-33 Mb on chromosome 3, for which all affected dogs were homozygous for a common haplotype. Microsatellite markers were developed in the candidate region for linkage analysis that resulted in a logarithm of odds score suggestive of linkage. The candidate region contains 29 genes, none of which are known to cause ataxia.

Altered sex hormone concentrations and gonadal mRNA expression levels of activin signaling factors in hatchling alligators from a contaminated Florida lake

Activins and estrogens participate in regulating the breakdown of ovarian germ cell nests and follicle assembly in mammals. In 1994, our group reported elevated frequencies of abnormal, multioocytic ovarian follicles in 6 month old, environmental contaminant-exposed female alligators after gonadotropin challenge. Here, we investigated if maternal contribution of endocrine disrupting contaminants to the egg subsequently alters estrogen/inhibin/activin signaling in hatchling female offspring, putatively predisposing an increased frequency of multioocytic follicle formation. We quantified basal and exogenous gonadotropin-stimulated concentrations of circulating plasma steroid hormones and ovarian activin signaling factor mRNA abundance in hatchling alligators from the same contaminated (Lake Apopka) and reference (Lake Woodruff) Florida lakes, as examined in 1994. Basal circulating plasma estradiol and testosterone concentrations were greater in alligators from the contaminated environment, whereas activin/inhibin betaA subunit and follistatin mRNA abundances were lower than values measured in ovaries from reference lake animals. Challenged, contaminant-exposed animals showed a more robust increase in plasma estradiol concentration following an acute follicle stimulating hormone (FSH) challenge compared with reference site alligators. Aromatase and follistatin mRNA levels increased in response to an extended FSH challenge in the reference site animals, but not in the contaminant-exposed animals. In hatchling alligators, ovarian follicles have not yet formed; therefore, these endocrine differences are likely to affect subsequent ovarian development, including ovarian follicle assembly.

Phylogenomic analyses reveal the evolutionary origin of the inhibin alpha-subunit, a unique TGFbeta superfamily antagonist

Transforming growth factor-beta (TGFβ) homologues form a diverse superfamily that arose early in animal evolution and control cellular function through membrane-spanning, conserved serine-threonine kinases (RII and RI receptors). Activin and inhibin are related dimers within the TGFβ superfamily that share a common β-subunit. The evolution of the inhibin α-subunit created the only antagonist within the TGFβ superfamily and the only member known to act as an endocrine hormone. This hormone introduced a new level of complexity and control to vertebrate reproductive function. The novel functions of the inhibin α-subunit appear to reflect specific insertion-deletion changes within the inhibin β-subunit that occurred during evolution. Using phylogenomic analysis, we correlated specific insertions with the acquisition of distinct functions that underlie the phenotypic complexity of vertebrate reproductive processes. This phylogenomic approach presents a new way of understanding the structure-function relationships between inhibin, activin, and the larger TGFβ superfamily.