MLPA is a practical and complementary alternative to CMA for diagnostic testing in patients with autism spectrum disorders and identifying new candidate CNVs associated with autism

Background Autism spectrum disorder (ASD) is a complex heterogeneous developmental disease with a significant genetic background that is frequently caused by rare copy number variants (CNVs). Microarray-based whole-genome approaches for CNV detection are widely accepted. However, the clinical significance of most CNV is poorly understood, so results obtained using such methods are sometimes ambiguous. We therefore evaluated a targeted approach based on multiplex ligation-dependent probe amplification (MLPA) using selected probemixes to detect clinically relevant variants for diagnostic testing of ASD patients. We compare the reliability and efficiency of this test to those of chromosomal microarray analysis (CMA) and other tests available to our laboratory. In addition, we identify new candidate genes for ASD identified in a cohort of ASD-diagnosed patients. Method We describe the use of MLPA, CMA, and karyotyping to detect CNV in 92 ASD patients and evaluate their clinical significance. Result Pathogenic and likely pathogenic mutations were identified by CMA in eight (8.07% of the studied cohort) and 12 (13.04%) ASD patients, respectively, and in eight (8.07%) and four (4.35%) patients, respectively, by MLPA. The detected mutations include the 22q13.3 deletion, which was attributed to ring chromosome 22 formation based on karyotyping. CMA revealed a total of 91 rare CNV in 55 patients: eight pathogenic, 15 designated variants of unknown significance (VOUS)—likely pathogenic, 10 VOUS—uncertain, and 58 VOUS—likely benign or benign. MLPA revealed 18 CNV in 18 individuals: eight pathogenic, four designated as VOUS—likely pathogenic, and six designated as VOUS—likely benign/benign. Rare CNVs were detected in 17 (58.62%) out of 29 females and 38 (60.32%) out of 63 males in the cohort. Two genes, DOCK8 and PARK2, were found to be overlapped by CNV designated pathogenic, VOUS—likely pathogenic, or VOUS—uncertain in multiple patients. Moreover, the studied ASD cohort exhibited significant (p < 0.05) enrichment of duplications encompassing DOCK8. Conclusion Multiplex ligation-dependent probe amplification and CMA yielded concordant results for 12 patients bearing CNV designated pathogenic or VOUS—likely pathogenic. Unambiguous diagnoses were achieved for eight patients (corresponding to 8.7% of the total studied population) by both MLPA and CMA, for one (1.09%) patient by karyotyping, and for one (1.09%) patient by FRAXA testing. MLPA and CMA thus achieved identical reliability with respect to clinically relevant findings. As such, MLPA could be useful as a fast and inexpensive test in patients with syndromic autism. The detection rate of potentially pathogenic variants (VOUS—likely pathogenic) achieved by CMA was higher than that for MLPA (13.04% vs. 4.35%). However, there was no corresponding difference in the rate of unambiguous diagnoses of ASD patients. In addition, the results obtained suggest that DOCK8 may play a role in the etiology of ASD

Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis

BACKGROUND: Invasive ductal and lobular carcinomas (IDC and ILC) are the most common histological types of breast cancer. Clinical follow-up data and metastatic patterns suggest that the development and progression of these tumors are different. The aim of our study was to identify gene expression profiles of IDC and ILC in relation to normal breast epithelial cells. METHODS: We examined 30 samples (normal ductal and lobular cells from 10 patients, IDC cells from 5 patients, ILC cells from 5 patients) microdissected from cryosections of ten mastectomy specimens from postmenopausal patients. Fifty nanograms of total RNA were amplified and labeled by PCR and in vitro transcription. Samples were analysed upon Affymetrix U133 Plus 2.0 Arrays. The expression of seven differentially expressed genes (CDH1, EMP1, DDR1, DVL1, KRT5, KRT6, KRT17) was verified by immunohistochemistry on tissue microarrays. Expression of ASPN mRNA was validated by in situ hybridization on frozen sections, and CTHRC1, ASPN and COL3A1 were tested by PCR. RESULTS: Using GCOS pairwise comparison algorithm and rank products we have identified 84 named genes common to ILC versus normal cell types, 74 named genes common to IDC versus normal cell types, 78 named genes differentially expressed between normal ductal and lobular cells, and 28 named genes between IDC and ILC. Genes distinguishing between IDC and ILC are involved in epithelial-mesenchymal transition, TGF-beta and Wnt signaling. These changes were present in both tumor types but appeared to be more prominent in ILC. Immunohistochemistry for several novel markers (EMP1, DVL1, DDR1) distinguished large sets of IDC from ILC. CONCLUSION: IDC and ILC can be differentiated both at the gene and protein levels. In this study we report two candidate genes, asporin (ASPN) and collagen triple helix repeat containing 1 (CTHRC1) which might be significant in breast carcinogenesis. Besides E-cadherin, the proteins validated on tissue microarrays (EMP1, DVL1, DDR1) may represent novel immunohistochemical markers helpful in distinguishing between IDC and ILC. Further studies with larger sets of patients are needed to verify the gene expression profiles of various histological types of breast cancer in order to determine molecular subclassifications, prognosis and the optimum treatment strategies

Duplication of 9p24.3 in three unrelated patients and their phenotypes, considering affected genes, and similar recurrent variants

Abstract Background Recent studies suggest that duplication of the 9p24.3 chromosomal locus, which includes the DOCK8 and KANK1 genes, is associated with autism spectrum disorders (ASD), intellectual disability/developmental delay (ID/DD), learning problems, language disorders, hyperactivity, and epilepsy. Correlation between this duplication and the carrier phenotype needs further discussion. Methods In this study, three unrelated patients with ID/DD and ASD underwent SNP aCGH and MLPA testing. Similarities in the phenotypes of patients with 9p24.3, 15q11.2, and 16p11.2 duplications were also observed. Results All patients with ID/DD and ASD carried the 9p24.3 duplication and showed intragenic duplication of DOCK8. Additionally, two patients had ADHD, one was hearing impaired and obese, and one had macrocephaly. Inheritance of the 9p24.3 duplication was confirmed in one patient and his sibling. In one patient KANK1 was duplicated along with DOCK8. Carriers of 9p24.3, 15q11.2, and 16p11.2 duplications showed several phenotypic similarities, with ID/DD more strongly associated with duplication of 9p24.3 than of 15q11.2 and 16p11.2. Conclusion We concluded that 9p24.3 is a likely cause of ASD and ID/DD, especially in cases of DOCK8 intragenic duplication. DOCK8 is a likely causative gene, and KANK1 aberrations a modulator, of the clinical phenotype observed. Other modulators were not excluded

Non‐invasive prognostic protein biomarker signatures associated with colorectal cancer

The current management of colorectal cancer (CRC) would greatly benefit from non‐invasive prognostic biomarkers indicative of clinicopathological tumor characteristics. Here, we employed targeted proteomic profiling of 80 glycoprotein biomarker candidates across plasma samples of a well‐annotated patient cohort with comprehensive CRC characteristics. Clinical data included 8‐year overall survival, tumor staging, histological grading, regional localization, and molecular tumor characteristics. The acquired quantitative proteomic dataset was subjected to the development of biomarker signatures predicting prognostic clinical endpoints. Protein candidates were selected into the signatures based on significance testing and a stepwise protein selection, each within 10‐fold cross‐validation. A six‐protein biomarker signature of patient outcome could predict survival beyond clinical stage and was able to stratify patients into groups of better and worse prognosis. We further evaluated the performance of the signature on the mRNA level and assessed its prognostic value in the context of previously published transcriptional signatures. Additional signatures predicting regional tumor localization and disease dissemination were also identified. The integration of rich clinical data, quantitative proteomic technologies, and tailored computational modeling facilitated the characterization of these signatures in patient circulation. These findings highlight the value of a simultaneous assessment of important prognostic disease characteristics within a single measurement.ISSN:1757-4676ISSN:1757-468

Circulating tumor nucleic acids: biology, release mechanisms, and clinical relevance

Abstract Background Despite advances in early detection and therapies, cancer is still one of the most common causes of death worldwide. Since each tumor is unique, there is a need to implement personalized care and develop robust tools for monitoring treatment response to assess drug efficacy and prevent disease relapse. Main body Recent developments in liquid biopsies have enabled real-time noninvasive monitoring of tumor burden through the detection of molecules shed by tumors in the blood. These molecules include circulating tumor nucleic acids (ctNAs), comprising cell-free DNA or RNA molecules passively and/or actively released from tumor cells. Often highlighted for their diagnostic, predictive, and prognostic potential, these biomarkers possess valuable information about tumor characteristics and evolution. While circulating tumor DNA (ctDNA) has been in the spotlight for the last decade, less is known about circulating tumor RNA (ctRNA). There are unanswered questions about why some tumors shed high amounts of ctNAs while others have undetectable levels. Also, there are gaps in our understanding of associations between tumor evolution and ctNA characteristics and shedding kinetics. In this review, we summarize current knowledge about ctNA biology and release mechanisms and put this information into the context of tumor evolution and clinical utility. Conclusions A deeper understanding of the biology of ctDNA and ctRNA may inform the use of liquid biopsies in personalized medicine to improve cancer patient outcomes

Non‐invasive prognostic protein biomarker signatures associated with colorectal cancer

The current management of colorectal cancer (CRC) would greatly benefit from non-invasive prognostic biomarkers indicative of clinicopathological tumor characteristics. Here, we employed targeted proteomic profiling of 80 glycoprotein biomarker candidates across plasma samples of a well-annotated patient cohort with comprehensive CRC characteristics. Clinical data included 8-year overall survival, tumor staging, histological grading, regional localization, and molecular tumor characteristics. The acquired quantitative proteomic dataset was subjected to the development of biomarker signatures predicting prognostic clinical endpoints. Protein candidates were selected into the signatures based on significance testing and a stepwise protein selection, each within 10-fold cross-validation. A six-protein biomarker signature of patient outcome could predict survival beyond clinical stage and was able to stratify patients into groups of better and worse prognosis. We further evaluated the performance of the signature on the mRNA level and assessed its prognostic value in the context of previously published transcriptional signatures. Additional signatures predicting regional tumor localization and disease dissemination were also identified. The integration of rich clinical data, quantitative proteomic technologies, and tailored computational modeling facilitated the characterization of these signatures in patient circulation. These findings highlight the value of a simultaneous assessment of important prognostic disease characteristics within a single measurement