Clinical Management of Neuroendocrine Neoplasms in Clinical Practice: A Formal Consensus Exercise

Many treatment approaches are now available for neuroendocrine neoplasms (NENs). While several societies have issued guidelines for diagnosis and treatment of NENs, there are still areas of controversy for which there is limited guidance. Expert opinion can thus be of support where firm recommendations are lacking. A group of experts met to formulate 14 statements relative to diagnosis and treatment of NENs and presented herein. The nominal group and estimate-talk-estimate techniques were used. The statements covered a broad range of topics from tools for diagnosis to follow-up, evaluation of response, treatment efficacy, therapeutic sequence, and watchful waiting. Initial prognostic characterization should be based on clinical information as well as histopathological analysis and morphological and functional imaging. It is also crucial to optimize RLT for patients with a NEN starting from accurate characterization of the patient and disease. Follow-up should be patient/tumor tailored with a shared plan about timing and type of imaging procedures to use to avoid safety issues. It is also stressed that patient-reported outcomes should receive greater attention, and that a multidisciplinary approach should be mandatory. Due to the clinical heterogeneity and relative lack of definitive evidence for NENs, personalization of diagnostic–therapeutic work-up is crucial

A recurrent F8 mutation (c.6046C>T) causing hemophilia A in 8% of northern Italian patients : evidence for a founder effect

Hemophilia A is a heterogeneous hemorrhagic disorder caused by a large number of mutations. Recurrent mutations are rare, except intron 22 and intron 1 inversions. The substitution of a cytosine to a thymine at nucleotide 6046 in F8 gene was identified in a group of Italian patients affected by hemophilia A from a specific region of Northern Italy with a prevalence of 7.6%. This F8 variant was the second most frequent mutation in our cohort, after the intron 22 inversion. The identification of the same mutation in a restricted population gets to suppose the existence of a founder effect. Intragenic and extragenic polymorphic markers were tested to assess this assumption. A peculiar haplotype in linkage disequilibrium with this recurrent mutation (c.6046C>T) was identified in 71% of patients, supporting a founder effect. This distinctive haplotype was not identified in a control group (Fisher's exact test, P\ua0<\ua00.0001), coming from the same geographic region. These data strongly suggested the presence of a founder effect, supporting the existence of a single mutation event. Using DMLE+2.3 software and the mathematical approach described by Bengtsson and Thomson, the inferred age of this mutation is supposed to be about 2325\ua0years (95% CI: 904-5081) ago

Phase 3 Trial of 177Lu-Dotatate for Midgut Neuroendocrine Tumors

Background Patients with advanced midgut neuroendocrine tumors who have had disease progression during first-line somatostatin analogue therapy have limited therapeutic options. This randomized, controlled trial evaluated the efficacy and safety of lutetium-177 (177Lu)-Dotatate in patients with advanced, progressive, somatostatin-receptor-positive midgut neuroendocrine tumors. Methods We randomly assigned 229 patients who had well-differentiated, metastatic midgut neuroendocrine tumors to receive either 177Lu-Dotatate (116 patients) at a dose of 7.4 GBq every 8 weeks (four intravenous infusions, plus best supportive care including octreotide long-acting repeatable [LAR] administered intramuscularly at a dose of 30 mg) (177Lu-Dotatate group) or octreotide LAR alone (113 patients) administered intramuscularly at a dose of 60 mg every 4 weeks (control group). The primary end point was progression-free survival. Secondary end points included the objective response rate, overall survival, safety, and the side-effect profile. The final analysis of overall survival will be conducted in the future as specified in the protocol; a prespecified interim analysis of overall survival was conducted and is reported here. Results At the data-cutoff date for the primary analysis, the estimated rate of progression-free survival at month 20 was 65.2% (95% confidence interval [CI], 50.0 to 76.8) in the 177Lu-Dotatate group and 10.8% (95% CI, 3.5 to 23.0) in the control group. The response rate was 18% in the 177Lu-Dotatate group versus 3% in the control group (P<0.001). In the planned interim analysis of overall survival, 14 deaths occurred in the 177Lu-Dotatate group and 26 in the control group (P=0.004). Grade 3 or 4 neutropenia, thrombocytopenia, and lymphopenia occurred in 1%, 2%, and 9%, respectively, of patients in the 177Lu-Dotatate group as compared with no patients in the control group, with no evidence of renal toxic effects during the observed time frame. Conclusions Treatment with 177Lu-Dotatate resulted in markedly longer progression-free survival and a significantly higher response rate than high-dose octreotide LAR among patients with advanced midgut neuroendocrine tumors. Preliminary evidence of an overall survival benefit was seen in an interim analysis; confirmation will be required in the planned final analysis. Clinically significant myelosuppression occurred in less than 10% of patients in the 177Lu-Dotatate group. (Funded by Advanced Accelerator Applications; NETTER-1 ClinicalTrials.gov number, NCT01578239 ; EudraCT number 2011-005049-11

Methodological framework for radiomics applications in Hodgkin’s lymphoma

Background: According to published data, radiomics features differ between lesions of refractory/relapsing HL patients from those of long-term responders. However, several methodological aspects have not been elucidated yet. Purpose: The study aimed at setting up a methodological framework in radiomics applications in Hodgkin’s lymphoma (HL), especially at (a) developing a novel feature selection approach, (b) evaluating radiomic intra-patient lesions’ similarity, and (c) classifying relapsing refractory (R/R) vs non-(R/R) patients. Methods: We retrospectively included 85 patients (male:female = 52:33; median age 35 years, range 19–74). LIFEx (www.lifexsoft.org) was used for [18F]FDG-PET/CT segmentation and feature extraction. Features were a-priori selected if they were highly correlated or uncorrelated to the volume. Principal component analysis-transformed features were used to build the fingerprints that were tested to assess lesions’ similarity, using the silhouette. For intra-patient similarity analysis, we used patients having multiple lesions only. To classify patients as non-R/R and R/R, the fingerprint considering one single lesion (fingerprint_One) and all lesions (fingerprint_All) was tested using Random Undersampling Boosting of Tree Ensemble (RUBTE). Results: HL fingerprints included up to 15 features. Intra-patient lesion similarity analysis resulted in mean/median silhouette values below 0.5 (low similarity especially in the non-R/R group). In the test set, the fingerprint_One classification accuracy was 62% (78% sensitivity and 53% specificity); the classification by RUBTE using fingerprint_All resulted in 82% accuracy (70% sensitivity and 88% specificity). Conclusions: Lesion similarity analysis was developed, and it allowed to demonstrate that HL lesions were not homogeneous within patients in terms of radiomics signature. Therefore, a random target lesion selection should not be adopted for radiomics applications. Moreover, the classifier to predict R/R vs non-R/R performed the best when all the lesions were used

Methodological framework for radiomics applications in Hodgkin’s lymphoma

According to published data, radiomics features differ between lesions of refractory/relapsing HL patients from those of long-term responders. However, several methodological aspects have not been elucidated yet. The study aimed at setting up a methodological framework in radiomics applications in Hodgkin’s lymphoma (HL), especially at (a) developing a novel feature selection approach, (b) evaluating radiomic intra-patient lesions’ similarity, and (c) classifying relapsing refractory (R/R) vs non-(R/R) patients. We retrospectively included 85 patients (male:female = 52:33; median age 35 years, range 19–74). LIFEx (www.lifexsoft.org) was used for [18F]FDG-PET/CT segmentation and feature extraction. Features were a-priori selected if they were highly correlated or uncorrelated to the volume. Principal component analysis transformed features were used to build the fingerprints that were tested to assess lesions’ similarity, using the silhouette. For intra-patient similarity analysis, we used patients having multiple lesions only. To classify patients as non-R/R and R/R, the fingerprint considering one single lesion (fingerprint_One) and all lesions (fingerprint_All) was tested using Random Undersampling Boosting of Tree Ensemble (RUBTE). HL fingerprints included up to 15 features. Intra-patient lesion similarity analysis resulted in mean/median silhouette values below 0.5 (low similarity especially in the non-R/R group). In the test set, the fingerprint_One classification accuracy was 62% (78% sensitivity and 53% specificity); the classification by RUBTE using fingerprint_All resulted in 82% accuracy (70% sensitivity and 88% specificity). Lesion similarity analysis was developed, and it allowed to demonstrate that HL lesions were not homogeneous within patients in terms of radiomics signature. Therefore, a random target lesion selection should not be adopted for radiomics applications. Moreover, the classifier to predict R/R vs non-R/R performed the best when all the lesions were used

miR-451a is underexpressed and targets AKT/mTOR pathway in papillary thyroid carcinoma

Papillary Thyroid Carcinoma (PTC) is the most frequent thyroid cancer. Although several PTC-specific miRNA profiles have been reported, only few upregulated miRNAs are broadly recognized, while less consistent data are available about downregulated miRNAs. In this study we investigated miRNA deregulation in PTC by miRNA microarray, analysis of a public dataset from The Cancer Genome Atlas (TCGA), literature review and meta-analysis based on a univocal miRNA identifier derived from miRBase v21. A list of 18 miRNAs differentially expressed between PTC and normal thyroid was identified and validated in the TCGA dataset. Furthermore, we compared our signature with miRNA profiles derived from 15 studies selected from literature. Then, to select possibly functionally relevant miRNA, we integrated our miRNA signature with those from two in vitro cell models based on the PTC-driving oncogene RET/PTC1. Through this strategy, we identified commonly deregulated miRNAs, including miR-451a, which emerged also by our meta-analysis as the most frequently reported downregulated miRNA. We showed that lower expression of miR-451a correlates with aggressive clinical-pathological features of PTC as tall cell variant, advanced stage and extrathyroid extension. In addition, we demonstrated that ectopic expression of miR-451a impairs proliferation and migration of two PTC-derived cell lines, reduces the protein levels of its recognized targets MIF, c-MYC and AKT1 and attenuates AKT/mTOR pathway activation.Overall, our study provide both an updated overview of miRNA deregulation in PTC and the first functional evidence that miR-451a exerts tumor suppressor functions in this neoplasia

DNA copy number changes in young gastric cancer patients with special reference to chromosome 19

Only a few cytogenetic and genetic studies have been performed in gastric cancer patients in young age groups. In the present study we used the comparative genomic hybridisation (CGH) method to characterise frequent DNA copy number changes in 22 gastric cancer patients of 45 years or younger and three gastric cancer cell lines established from patients younger than 45 years. Analysis of DNA copy number changes revealed frequent DNA copy number increases at chromosomes 17q (52%), 19q (68%) and 20q (64%). To confirm the CGH results and to characterise the amplicon region on the most frequently amplified chromosome, chromosome 19, we carried out fluorescence in situ hybridisation (FISH) analysis and Southern blot analysis. Fluorescence in situ hybridisation with the bacterial artificial chromosome (BAC) clone mapped to 19q12 indicated a copy number increase in all eight tumour specimens studied. Southern blot analysis of six tumour specimens and three tumour cell lines, with five probes mapped to the 19q12-13.2 region, suggested cyclin E to be one of the candidate target genes in the 19q region for gastric cancer tumorigenesis. Cyclin E protein overexpression was verified in tumours with amplification on chromosome 19. Further studies are required to investigate the biological and clinical significance of 19q amplicon and cyclin E upregulation in gastric cancer of young patient

Minimally-invasive treatments for benign thyroid nodules: recommendations for information to patients and referring physicians by the Italian Minimally-Invasive Treatments of the Thyroid group

Purpose: In this paper, the members of the Italian Working Group on Minimally-Invasive Treatments of the Thyroid (MITT group) aim to summarize the most relevant information that could be of help to referring physicians and that should be provided to patients when considering the use of MITT for the treatment of benign thyroid nodules. Methods: An interdisciplinary board of physicians with specific expertise in the management of thyroid nodules was appointed by the Italian MITT Group. A systematic literature search was performed, and an evidence-based approach was used, including also the knowledge and the practical experience of the panelists to develop the paper. Results: The paper provides a list of questions that are frequently asked by patients to operators performing MITT, each with a brief and detailed answer and more relevant literature references to be consulted. Conclusions: This paper summarizes the most relevant information to be provided to patients and general practitioners/referring physicians about the use of MITT for the treatment of benign thyroid nodules

Building pathway clusters from Random Forests classification using class votes

<p>Abstract</p> <p>Background</p> <p>Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.</p> <p>Results</p> <p>We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster.</p> <p>Conclusion</p> <p>Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.</p