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Background: Breast cancer is the most frequently diagnosed cancer in women and about 10% of breast cancer cases are hereditary. BRCA1 and BRCA2 are the genes most frequently associated with Hereditary Breast Cancer, although there are numerous other genes, such as PALB2, CHEK2 and ATM, that require to be considered as well. Germline Copy Number Variation (CNV) is one mutation type that is an important contributor to hereditary breast cancer. Nowadays, next-generation sequencing (NGS) technologies has contributed to multi-gene panel analysis used in clinical practice. Methods: In total, 1418 individuals were tested for breast cancer predisposition, using a solution-based capture approach. Targeted NGS was performed with a panel of 36 genes. The capture-based approach allowed for computational analysis of CNVs from NGS data. Results: We investigate the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and the non-commercial tool panelcn.MOPS. Both algorithms are specifically developed for CNV analysis of sequencing data reporting 99-100% sensitivity and up to 100% specificity for the prediction of CNVs up to the level of a single gene exon. All CNVs detected with these algorithms were then verified experimentally using the MLPA technique as an orthogonal assay. At least one pathogenic/likely pathogenic variant was identified in 289 samples (20.4%). CNVs accounted for 10.4% (30/289), referring to the deletion of one or more exons of a gene. Interestingly, 50% of deletions were single exon and approximately 36% of CNVs were detected in genes other than BRCA1/2. In specific, of the 30 CNVs detected, 60% occurred in BRCA1, 3.3% in BRCA2, 20% in CHEK2, 6.7% in FANCA, 6.7% in PMS2, and 3.3% in ATM. The majority of CNVs in BRCA1 were deletions of exons 19, 22, and 22-23 whereas deletions of exons 9-10 were the most common deletions in CHEK2. Detailed information of all CNVs detected is provided in Table 1. Conclusions: Our results suggest that CNV analysis should not be restricted to BRCA1/2 due to the significant proportion of CNVs (36%) in additional breast cancer predisposition genes. Furthermore, in silico CNV detection tools provide a cost-effective and feasible methodology for the identification of CNVs from NGS experiments. This outlines the clinical utility of comprehensive genetic testing that includes full sequencing and CNV analysis in hereditary breast cancer facilitating personalized management decisions for patients. Table 1.Pathogenic Copy Number Variations (CNVs) identified in this studyGeneHGVS nomenclatureOther nomenclature# detectedATMNM_000051:c.(-30+1_-29-1)_(331+1_332-1)deldeletion of exons 2-41BRCA1NM_007294:c.(5467+1_5468-1)-(*1_?)deldeletion of exon 237BRCA1NM_007294:c.(5406+1_5407-1)_(*1_?)deldeletion of exons 23-245BRCA1NM_007294:c.(5193+1_5194-1)-(5277+1_5278-1)deldeletion of exon 196BRCA2NM_000059:c.(6841+1_6842-1)_(7007+1_7008-1)deldeletion of exons 12-131CHEK2NM_007194:c.(908+1_909-1)_(1095+1_1096-1)deldeletion of exons 9-104CHEK2NM_007194:c.(792+1_793-1)_(846+1_847-1)deletion of exon 72FANCANM_000135:c.(1626+1_1627-1)_ (2852+1_2853-1)deldeletion of exons 18-291FANCANM_000135:c.(893+1_894-1)_(1359+1_1360-1)deldeletion of exons 11-141PMS2NM_000535: c.(903+1_904-1)_(988+1_989-1)deldeletion of exon 91PMS2NM_000535:c.(705+1_706-1)_(2006+1_2007-1)deldeletion of exons 7-111 Citation Format: Nikolaos Tsoulos, Konstantinos Agiannitopoulos, Georgia Pepe, Eirini Papadopoulou, Georgios N Tsaousis, Despina Apostolopoulou, Angeliki Meintani, Vassileios Venizelos, Christos Markopoulos, Rodoniki Iosifidou, Sofia Karageorgopoulou, Christos Christodoulou, Ioannis Natsiopoulos, Konstantinos Papazisis, Maria Vasilaki-Antonatou, Eleftherios Kabletsas, Amanta Psyrri, Stylianos Giassas, Dimitrios Ziogas, Efthalia Lalla, Anna Koumarianou, Christos Papadimitriou, Vahit Ozmen, Sualp Tansan, Kerim Kaban, Tahsin Ozatlı, Dan Tudor Eniu, Angelica Chiorean, Alexandru Blidaru, George Nasioulas. Different CNVs account for 10.4% of pathogenic variants in 1418 patients referred for hereditary breast cancer testing [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-10.

Male breast cancer (MBC) is a very rare disorder affecting approximately 1 in 833 men. Genetic predisposition is one of the most important risk factors of MBC with BRCA2 being the most commonly mutated gene in males diagnosed with breast cancer. However, a large part of MBC heritability is still unexplained. This study sought to add to the data already available on the genetics of MBC.Our study initially involved comprehensive analysis of BRCA1 and BRCA2, followed by analysis of 43 genes implicated in cancer predisposition in a series of 100 Greek patients diagnosed with MBC between 1995-2015.Pathogenic variants were identified in 13 patients, with BRCA2 being the most commonly affected gene, followed by BRCA1, RAD50, RAD51B, and MSH3.In agreement with previous reports, BRCA2 is the most important genetic factor of MBC predisposition, while the remaining known cancer predisposition genes are each very rarely involved, rendering conclusions as to their cumulative effect difficult to draw.

Objective Several microRNA (miRNA) polymorphisms have been associated with susceptibility to specific health disorders, including cardiovascular diseases. The aim of the present study was to investigate whether four well-studied miRNA polymorphisms in non-Caucasian populations, namely miR146a G>C (rs2910164), miR149 C>T (rs2292832), miR196a2 C>T (rs11614913) and miR499 A>G (rs3746444), contribute to the risk for the development of premature Coronary Artery Disease (CAD) in the Greek population. Methods We used a case-control study to examine these associations in 400 individuals: 200 CAD patients [including a subgroup of myocardial infraction (MI) patients] and 200 healthy controls, all of Greek origin. MiRNA polymorphisms were genotyped using three different assays: Polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP), High resolution Melting (HRM) and Sanger sequencing. Results Two of these polymorphisms, miR196a2 C>T (rs11614913) and miR499 A>G (rs3746444) were found to be strongly associated with increased risk for CAD (p=0.0388 and p=0.0013, respectively) and for MI (p=0.0281 and p=0.0273, respectively). Furthermore, miR146C-miR149C-miR196T-miR499G allele combination appeared to be significantly related to CAD (p=0.0185) and MI (p=0.0337) prevalence. Conclusions Our results suggest that at least two of the studied polymorphisms, miR196a2 C>T (rs11614913) and miR499 A>G (rs3746444), as well as the miR146C-miR149C-miR196T-miR499G allele combination could represent useful biomarkers of CAD and/or MI susceptibility in the Greek population. These special genetic characteristics, in combination with environmental factors and personal habits, might contribute to CAD and/or MI prevalence.

Background Tumor molecular profile analysis by Next Generation Sequencing technology is currently widely applied in clinical practice and has enabled the detection of predictive biomarkers of response to targeted treatment. In parallel with targeted therapies, immunotherapies are also evolving, revolutionizing cancer therapy, with Programmed Death-ligand 1 (PD-L1), Microsatellite instability (MSI), and Tumor Mutational Burden (TMB) analysis being the biomarkers employed most commonly. Methods In the present study, tumor molecular profile analysis was performed using a 161 gene NGS panel, containing the majority of clinically significant genes for cancer treatment selection. A variety of tumor types have been analyzed, including aggressive and hard to treat cancers such as pancreatic cancer. Besides, the clinical utility of immunotherapy biomarkers (TMB, MSI, PD-L1), was also studied. Results Molecular profile analysis was conducted in 610 cancer patients, while in 393 of them a at least one biomarker for immunotherapy response was requested. An actionable alteration was detected in 77.87% of the patients. 54.75% of them received information related to on-label or off-label treatment (Tiers 1A.1, 1A.2, 2B, and 2C.1) and 21.31% received a variant that could be used for clinical trial inclusion. The addition to immunotherapy biomarker to targeted biomarkers’ analysis in 191 cases increased the number of patients with an on-label treatment recommendation by 22.92%, while an option for on-label or off-label treatment was provided in 71.35% of the cases. Conclusions Tumor molecular profile analysis using NGS is a first-tier method for a variety of tumor types and provides important information for decision making in the treatment of cancer patients. Importantly, simultaneous analysis for targeted therapy and immunotherapy biomarkers could lead to better tumor characterization and offer actionable information in the majority of patients. Furthermore, our data suggest that one in two patients may be eligible for on-label ICI treatment based on biomarker analysis. However, appropriate interpretation of results from such analysis is essential for implementation in clinical practice and accurate refinement of treatment strategy.

Background Classification of splicing variants (SVs) in genes associated with hereditary cancer is often challenging. The aim of this study was to investigate the occurrence of SVs in hereditary cancer genes and the clinical utility of RNA analysis. Material and methods 1518 individuals were tested for cancer predisposition, using a Next Generation Sequencing (NGS) panel of 36 genes. Splicing variant analysis was performed using RT-PCR and Sanger Sequencing. Results In total, 34 different SVs were identified, 53% of which were classified as pathogenic or likely pathogenic. The remaining 16 variants were initially classified as Variant of Uncertain Significance (VUS). RNA analysis was performed for 3 novel variants. Conclusion The RNA analysis assisted in the reclassification of 20% of splicing variants from VUS to pathogenic. RNA analysis is essential in the case of uncharacterized splicing variants, for proper classification and personalized management of these patients.

Background/Aim: The use of multi-gene panels for germline testing in breast cancer enables the estimation of cancer risk and guides risk-reducing management options. The aim of this study was to present data that demonstrate the different levels of actionability for multi-gene panels used in genetic testing of breast cancer patients and their family members. Materials and Methods: We performed an analysis in our clinical database to identify breast cancer patients undergoing genetic testing. We reviewed positive results in respect of risk estimation and management, cascade family testing, secondary findings and information for treatment decision-making. Results: A total of 415 positive test reports were identified with 57.1%, 18.1%, 10.8% and 13.5% of individuals having pathogenic/likely pathogenic variants in high, moderate, low and with insufficient evidence for breast cancer risk genes, respectively. Six point seven percent of individuals were double heterozygotes. Conclusion: Germline findings in 92% of individuals are linked to evidence-based treatment information and risk estimates for predisposition to breast and/or other cancer types. The use of germline findings for treatment decision making expands the indication of genetic testing to include individuals that could benefit from targeted treatments.

To determine whether gene polymorphisms which are associated with age-related macular degeneration (AMD) influence treatments’ response and specifically the antioxidant supplementation in dry AMD patients, as well as the anti-vascular endothelial growth factor (anti-VEGF) therapy in neovascular AMD patients. A total of 170 patients with dry AMD and 52 neovascular AMD patients were genotyped for the following single nucleotide polymorphisms (SNPs): rs1061170/Y402H in CFH gene, rs10490924/A69S in ARMS2 gene, rs9332739/E318D and rs547154/IVS10 in C2 gene, and rs4151667/L9H and rs2072633/IVS17 in CFB gene. Treatment response was evaluated by comparing visual acuity and optical coherence tomography between baseline and at the end of the treatment. Τhe CFH/Y402H variant was associated with the response to antioxidants in dry AMD patients. Carriers of one or two CFH risk alleles displayed a lower chance of responding compared to those with no risk allele. No association of antioxidants’ response and ARMS2/A69S genotype was identified. The analysis of the C2 and CFB genetic variants (protective SNPs) revealed that antioxidant supplementation was much more effective in protective SNP carriers. In neovascular AMD patients, the analysis indicated that Y402H homozygous patients were less likely to respond to anti-VEGF therapy compared to heterozygous. Regarding the ARMS2/A69S genotype, carriers of the risk variant experienced significantly worse treatment outcome compared to wild-type patients. In AMD patients, the efficacy of the antioxidant supplementation and the anti-VEGF therapy appears to differ by genotype. The detection of genetic variants, associated with treatment responsiveness, could lead to improved visual outcomes through genotype-directed therapy.

Background Carriers with pathogenic variants in MSH2 have increased risk to develop colorectal, endometrium, ovarian, and other types of cancer. The PALB2 is associated with breast, ovarian, pancreatic, and prostate cancer. We describe the case of a 42‐year‐old female diagnosed with endometrial cancer at the age of 42 years with a strong family history of colorectal cancer, which was referred to our private diagnostic laboratory for genetic testing. Methods In this study, we performed next‐generation sequencing (NGS) using an amplicon based 26 genes panel. The presence of multi‐exonic copy number variations (CNVs) was investigated by computational analysis and Multiplex Ligation‐dependent Probe Amplification (MLPA). Results A gross deletion of the genomic region encompassing exons 11–16 of the MSH2 and the loss‐of‐function variant c.757_758delCT, p.(Leu253Ilefs*3) in the PALB2 were identified in the proband. Conclusions Multigene analysis using NGS technology allows the identification of pathogenic variants in genes that would normally not be tested based on the patient diagnosis. In our case these results explained not only the personal and/or family history of cancer but also allowed the surveillance for prevention of other cancer types. Moreover, the detection of large genomic rearrangements should be routinely included in hereditary cancer testing., We describe the case of a 42‐year‐old female diagnosed with endometrial cancer with a strong family history of colorectal cancer, which was referred to our private diagnostic laboratory for genetic testing. By next‐generation sequencing (NGS) and Multiplex Ligation‐dependent Probe Amplification (MLPA) analysis we identified a gross deletion of the genomic region encompassing exons 11–16 of the MSH2 gene and the loss‐of‐function variant c.757_758delCT, p.(Leu253Ilefs*3) in the PALB2 gene in our proband.

The majority of all proteins in cells interact with membranes either permanently or temporarily. Peripheral membrane proteins form transient complexes with membrane proteins and/or lipids, via non-covalent interactions and are of outmost importance, due to numerous cellular functions in which they participate. In an effort to collect data regarding this heterogeneous group of proteins we designed and constructed a database, called PerMemDB. PerMemDB is currently the most complete and comprehensive repository of data for eukaryotic peripheral membrane proteins deposited in UniProt or predicted with the use of MBPpred - a computational method that specializes in the detection of proteins that interact non-covalently with membrane lipids, via membrane binding domains. The first version of the database contains 231,770 peripheral membrane proteins from 1009 organisms. All entries have cross-references to other databases, literature references and annotation regarding their interactions with other proteins. Moreover, additional sequence annotation of the characteristic domains that allow these proteins to interact with membranes is available, due to the application of MBPpred. Through the web interface of PerMemDB, users can browse the contents of the database, submit advanced text searches and BLAST queries against the protein sequences deposited in PerMemDB. We expect this repository to serve as a source of information that will allow the scientific community to gain a deeper understanding of the evolution and function of peripheral membrane proteins via the enhancement of proteome-wide analyses. The database is available at: http://bioinformatics.biol.uoa.gr/db=permemdb.

Background CHEK2 is involved in the DNA damage repair response Fanconi anemia (FA)-BRCA pathway. An increased risk for breast and other cancers has been documented in individuals who carry a single pathogenic CHEK2 variant. As for other genes involved in cancer predisposition, different types of pathogenic variants have been observed, including single nucleotide variations, short insertions/deletions, large genomic rearrangements and splicing variants. Splicing variants occurring in the splicing acceptor or donor site result in alternative mature mRNA produced and can cause intron retention, exon skipping, or creation of alternative 3′ and 5′ splice site. Thus, the pathogenicity of this type of alterations should always be explored experimentally and their effect in the mRNA and consequently the protein produced, should be defined. The aim of this study was the delineation of the effect of a splicing variant in the CHEK2 gene. Case presentation A healthy 28-year-old woman with a family history of breast and ovarian cancer was referred for genetic testing. The variant c.793-1G > A (rs730881687) was identified by Next Generation Sequencing (NGS) using a solution-based capture method, targeting 33 cancer predisposition genes (SeqCap EZ Probe library, Roche NimbleGen). Experimental analysis in patient-derived leukocytes using RT-PCR of mRNA followed by cDNA sequencing revealed the deletion of one base from the alternative transcript created (r.793del). This resulted in a frameshift leading to premature termination codon within exon 7 (p.(Asp265Thrfs*10)). Conclusions This finding suggests that the CHEK2 splicing variant c.793-1G > A is a deleterious variant. Our case shows that RNA analysis is a valuable tool for uncharacterized splice site variants in individuals referred for testing and facilitates their personalized management.

Gastrointestinal malignancies are among the leading causes of cancer-related deaths worldwide. Like all human malignancies they are characterized by accumulation of mutations which lead to inactivation of tumor suppressor genes or activation of oncogenes. Advances in Molecular Biology techniques have allowed for more accurate analysis of tumors' genetic profiling using new breakthrough technologies such as next generation sequencing (NGS), leading to the development of targeted therapeutical approaches based upon biomarker-selection. During the last 10 years tremendous advances in the development of targeted therapies for patients with advanced cancer have been made, thus various targeted agents, associated with predictive biomarkers, have been developed or are in development for the treatment of patients with gastrointestinal cancer patients. This review summarizes the advances in the field of molecular biomarkers in tumors of the gastrointestinal tract, with focus on the available NGS platforms that enable comprehensive tumor molecular profile analysis.

The majority of all proteins in cells interact with membranes either permanently or temporarily. Peripheral membrane proteins form transient complexes with membrane proteins and/or lipids, via non-covalent interactions and are of outmost importance, due to numerous cellular functions in which they participate. In an effort to collect data regarding this heterogeneous group of proteins we designed and constructed a database, called PerMemDB. PerMemDB is currently the most complete and comprehensive repository of data for eukaryotic peripheral membrane proteins deposited in UniProt or predicted with the use of MBPpred – a computational method that specializes in the detection of proteins that interact non-covalently with membrane lipids, via membrane binding domains. The first version of the database contains 241173 peripheral membrane proteins from 1216 organisms. All entries have cross-references to other databases, literature references and annotation regarding their interactions with other proteins. Moreover, additional sequence annotation of the characteristic domains that allow these proteins to interact with membranes is available, due to the application of MBPpred. Through the web interface of PerMemDB, users can browse the contents of the database, submit advanced text searches and BLAST queries against the protein sequences deposited in PerMemDB. We expect this repository to serve as a source of information for the development of prediction algorithms regarding peripheral membrane proteins, in addition to proteome-wide analyses.Availabilityhttp://bioinformatics.biol.uoa.gr/permemdbContactveconom@biol.uoa.grSupplementary informationhttp://83.212.109.111:8085/assets/Nastou_Supplement.xlsx

BackgroundAnalysis of circulating tumor nucleic acids in plasma of Non-Small Cell Lung Cancer (NSCLC) patients is the most widespread and documented form of "liquid biopsy" and provides real-time information on the molecular profile of the tumor without an invasive tissue biopsy.MethodsLiquid biopsy analysis was requested by the referral physician in 121 NSCLC patients at diagnosis and was performed using a sensitive Next Generation Sequencing assay. Additionally, a comparative analysis of NSCLC patients at relapse following EGFR Tyrosine Kinase Inhibitor (TKIs) treatment was performed in 50 patients by both the cobas and NGS platforms.ResultsAt least one mutation was identified in almost 49% of the cases by the NGS approach in NSCLC patients analyzed at diagnosis. In 36 cases with paired tissue available a high concordance of 86.11% was observed for clinically relevant mutations, with a Positive Predictive Value (PPV) of 88.89%. Furthermore, a concordance rate of 82% between cobas and the NGS approach for the EGFR sensitizing mutations (in exons 18, 19, 21) was observed in patients with acquired resistance to EGFR TKIs, while this concordance was 94% for the p.T790M mutation, with NGS being able to detect this mutation in three 3 additional patients.ConclusionsThis study indicates the feasibility of circulating tumor nucleic acids (ctNA) analysis as a tumor biopsy surrogate in clinical practice for NSCLC personalized treatment decision making. The use of new sensitive NGS techniques can reliably detect tumor-derived mutations in liquid biopsy and provide clinically relevant information both before and after targeted treatment in patients with NSCLC. Thus, it could aid physicians in treatment decision making in clinical practice.

Non‑small cell lung cancer (NSCLC) is the most common type of lung cancer and a tumor with a broad spectrum of targeted therapies already available or in clinical trials. Thus, molecular characterization of the tumor using next generation sequencing (NGS) technology, has become a key tool for facilitating treatment decisions and the clinical management of NSCLC patients. The performance of a custom 23 gene multiplex amplification hot spot panel, based on Ion AmpliSeq™ technology, was evaluated for the analysis of tumor DNA extracted from formalin-fixed and paraffin-embedded (FFPE) tissues. Furthermore, the Ion AmpliSeq™ RNA Fusion Lung Cancer Research Panel was used for fusion RNA transcript analysis. The mutation spectrum of the tumors was determined in a cohort of 502 patients with NSCLC using the aforementioned targeted gene panels. The panel used for tumor DNA analysis in this study exhibited high rates (100%) of sensitivity, specificity and reproducibility at a mutation allelic frequency of 3%. At least one DNA mutation was detected in 374 patients (74.5%) and an RNA fusion was identified in 16 patients, (3.2%). In total, alterations in a cancer-driver gene were identified (including point mutations, gene rearrangements and MET amplifications) in 77.6% of the tumors tested. Among the NSCLC patients, 23% presented a mutation in a gene associated with approved or emerging targeted therapy. More specifically, 13.5% (68/502) presented a mutation in a gene with approved targeted therapy (EGFR, ALK, ROS1) and 9.4% (47/502) had an alteration in a gene related to emerging targeted therapies (ERBB2, BRAF, MET and RET). Furthermore, 51.6% of the patients had a mutation in a gene that could be related to an off label therapy or indicative for access to a clinical trial. Thus, the targeted NGS panel used in this study is a reliable approach for tumor molecular profiling and can be applied in personalized treatment decision making for NSCLC patients.

To investigate whether the missense rs605059 polymorphism of HSD17B1 gene, which is expressed mainly in the placenta, is associated with recurrent spontaneous abortions (RSA).This study group consisted of 138 women with three or more unexplained spontaneous abortions, before the 20th week of gestation, with the same partner, while 140 healthy women served as controls. To genotype the individuals, we used the polymerase chain reaction-restriction fragment length polymorphism method.The genotyping of the rs605059 polymorphism revealed the frequencies 0.22, 0.45 and 0.33, for AA, GA and GG genotypes, respectively, for the patient group and 0.37, 0.41 and 0.22, respectively, for the control group. The A allele frequencies were 0.44 and 0.57 for the patient and control group, respectively, and the G allele frequencies were 0.56 and 0.43 for the patient and control group, respectively. Statistical analysis of the results indicated the existence of significant differences in genotype and allele frequencies between the two groups.The rs605059 polymorphism of the HSD17B1 gene is associated with increased risk of RSA in our Caucasian Greek population. Thus it could be used as a prognostic genetic marker for RSA.

Background The application of the Next Generation Sequencing (NGS) technology has facilitated multigene panel testing for hereditary breast cancer (BC) in clinical practice. We performed a retrospective analysis of individuals referred for testing in our lab aiming to investigate the contribution of included genes and evaluate current genetic testing guidelines in BC. Methods In total, 1141 BC patients and 184 unaffected individuals with family history (FH) of BC were referred from physicians for testing using a multigene panel. Genomic DNA was enriched for targeted regions of 33 genes and sequencing was carried out using the Illumina NGS technology. The presence of large genomic rearrangements (LGRs) was investigated computationally and by Multiplex Ligation-dependent Probe Amplification (MLPA). Results A pathogenic variant (PV) was identified in 22% (291/1325) of analyzed individuals and in specific in 23.2% of BC patients and 14.1% of unaffected individuals (P = 0.006). Among individuals with PVs, 49.1% were located in the BRCA1/2 genes whereas 8.6%, 22.7% and 19.6% occurred in other high, moderate and low-risk genes respectively. Notably, 21 of the 291 positive individuals (7.2%) carried clinically significant variants in two different genes and 6.5% had a LGR. A retrospective analysis of positive individuals showed that 88.3% of BC patients met the NCCN criteria for further genetic risk evaluation compared to 80.8% of unaffected individuals with FH of BC (P = 0.269). In BRCA-positive cases, NCCN criteria were met in 92.3% of the referrals compared to 81.8% in individuals positive for other genes (P = 0.008). Conclusions Extended multigene panel testing in hereditary BC facilitates the detection of nearly twice as many individuals that could benefit from personalized management. In our cohort, the currently used selection criteria for HBOC failed to identify only 12.7% of individuals positive for pathogenic variants, suggesting strong selection strategies from physicians. However, our results indicate that selection criteria perform better for the identification of BRCA-positive BC patients and should be revised to facilitate towards the inclusion of BC patients with PVs in other genes. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure All authors have declared no conflicts of interest.

During the last two decades a large number of computational methods have been developed for predicting transmembrane protein topology. Current predictors rely on topogenic signals in the protein sequence, such as the distribution of positively charged residues in extra-membrane loops and the existence of N-terminal signals. However, phosphorylation and glycosylation are post-translational modifications (PTMs) that occur in a compartment-specific manner and therefore the presence of a phosphorylation or glycosylation site in a transmembrane protein provides topological information. We examine the combination of phosphorylation and glycosylation site prediction with transmembrane protein topology prediction. We report the development of a Hidden Markov Model based method, capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites along the protein sequence. Our method integrates a novel feature in transmembrane protein topology prediction, which results in improved performance for topology prediction and reliable prediction of phosphorylation and glycosylation sites. The method is freely available at http://bioinformatics.biol.uoa.gr/HMMpTM.

Transmembrane beta-barrels (TMBBs) constitute an important structural class of membrane proteins located in the outer membrane of gram-negative bacteria, and in the outer membrane of chloroplasts and mitochondria. They are involved in a wide variety of cellular functions and the prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes is of great importance as they are promising targets for antimicrobial drugs and vaccines. Several methods have been applied for the prediction of the transmembrane segments and the topology of beta barrel transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for beta barrel transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane beta strands of TMBBs and discriminating them from globular proteins.

Alpha helical transmembrane (TM) proteins constitute an important structural class of membrane proteins involved in a wide variety of cellular functions. The prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes, is of great importance for the elucidation of their structure and function. Several methods have been applied for the prediction of the transmembrane segments and the topology of alpha helical transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for alpha helical transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane alpha helices in proteins and discriminating them from globular proteins.

Transmembrane beta-barrels (TMBBs) constitute an important structural class of membrane proteins located in the outer membrane of gram-negative bacteria, and in the outer membrane of chloroplasts and mitochondria. They are involved in a wide variety of cellular functions and the prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes is of great importance as they are promising targets for antimicrobial drugs and vaccines. Several methods have been applied for the prediction of the transmembrane segments and the topology of beta barrel transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for beta barrel transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane beta strands of TMBBs and discriminating them from globular proteins.

Alpha helical transmembrane (TM) proteins constitute an important structural class of membrane proteins involved in a wide variety of cellular functions. The prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes, is of great importance for the elucidation of their structure and function. Several methods have been applied for the prediction of the transmembrane segments and the topology of alpha helical transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for alpha helical transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane alpha helices in proteins and discriminating them from globular proteins.

Germline mutations in the BRCA1 and BRCA2 genes are associated with hereditary predisposition to breast and ovarian cancer. Sensitive and accurate detection of BRCA1 and BRCA2 mutations is crucial for personalized clinical management of individuals affected by breast or ovarian cancer, and for the identification of at-risk healthy relatives. We performed molecular analysis of the BRCA1 and BRCA2 genes in 898 Greek families, using Sanger sequencing or Next Generation Sequencing for the detection of small insertion/deletion frameshift, nonsynonymous, truncating and splice-site alterations and MLPA for the detection of large genomic rearrangements. In total, a pathogenic mutation was identified in 12.9% of 898 families analyzed. Of the 116 mutations identified in total 9% were novel and 14.7% were large genomic rearrangements. Our results indicate that different types of mutational events in the BRCA1 and BRCA2 genes are responsible for the hereditary component of breast/ovarian cancer in the Greek population. Therefore the methodology used in the analysis of Greek patients must be able to detect both point and small frameshift mutations in addition to large genomic rearrangements across the entire coding region of the two genes.

BACKGOUND: Hereditary cancer predisposition syndromes are believed to be responsible for approximately 5-10% of all diagnosed cancer cases. In the past, single genes analysis of certain high risk genes was used for the determination of the genetic cause of cancer heritability in certain families. The selection of genes was mainly based on the family history of the individuals analyzed and included only highly associated genes (e.g. the BRCA1 and BRCA2 genes for families with breast cancer history. Nowadays though, the application of Next Generation Sequencing (NGS) technology has facilitated multigene panel analysis and is widely used in clinical practice, for the identification of individuals with cancer predisposition gene mutations. AIM: The aim of this study was to investigate the extent and nature of mutations in 36 genes implicated in hereditary cancer predisposition in individuals referred for testing in our lab. MATERIALS & METHODS: In total, 1197 individuals were referred for testing in our lab in the past four years from Greece, Romania and Turkey. The analysis of genes involved in hereditary cancer predisposition was performed using two NGS approaches. The first 451 individuals were analyzed using an amplicon based sequencing method (26 gene panel), while the following 746 individuals were analyzed using a capture based method (33 gene panel). Genomic DNA was enriched for targeted regions of 36 genes involved in hereditary predisposition to cancer included in both versions of the panel (APC, BMPR1A, BRCA1, BRCA2, CDH1, CDK4, CDKN2A, EPCAM, MEN1, MLH1, MSH2, MSH6, MUTYH, PALB2, PMS2, PTEN, RET, SMAD4, STK11, TP53, VHL, ATM, BRIP1, CHEK2, NBN, RAD51C, RAD51D, BARD1, BLM, CHEK1, ABRAXAS1 (FAM175A), MRE11 (MRE11A), NF1, RAD50, RAD51B, XRCC2). Sequencing was carried out using the Illumina NGS technology. Reads were aligned to the reference sequence (GRCh37), and sequence changes were identified and interpreted in the context of a single clinically relevant transcript. The presence of large genomic rearrangements was investigated by computational analysis of NGS results and the use of MLPA for 13 genes. All clinically significant observations were confirmed by orthogonal technologies. RESULTS: In total, a pathogenic mutation was identified in 259 of the 1197 individuals (21.6%) analyzed while a VUS was identified in 35.7% of the cases. Clinically significant mutations were identified in 29 of the genes analyzed. Concerning the mutation distribution among individuals with positive findings, 44.7% of them were located in BRCA1/2 genes whereas 20.9%, 19.9%, and 14.5% in high, moderate and low risk genes respectively. In addition to BRCA1 and BRCA2 genes other highly mutated genes were CHEK2 (10.6%), PALB2 (7.1%), MUTYH (7.1%) and ATM (4.3%). Of note is that 25 of the 259 positive individuals (9.7%) carried clinically significant mutations in two different genes and 5.8% had a large genomic rearrangement (LGR). CONCLUSIONS: Our results support the clinical significance of analysis of a panel of genes involved in hereditary cancer predisposition. In our cohort, analysis of this panel allowed for the identification of 8.3% additional pathogenic variants in moderate/low risk genes, enabling personalized management of these individuals. Citation Format: Tsoulos N, Tsaousis GN, Papadopoulou E, Agiannitopoulos K, Pepe G, Kambouri S, Apessos A, Diamantopoulos N, Floros T, Iosifidou R, Katopodi O, Koumarianou A, Markopoulos C, Papazisis K, Venizelos V, Xanthakis I, Xepapadakis G, Banu E, Eniu DT, Negru S, Stanculeanu DL, Ungureanu A, Ozmen V, Tansan S, Tekinel M, Yalcin S, Nasioulas G. Analysis of hereditary cancer syndromes by using a panel of genes: Novel and multiple pathogenic mutations [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-03-07.

A large number of modular domains that exhibit specific lipid binding properties are present in many membrane proteins involved in trafficking and signal transduction. These domains are present in either eukaryotic peripheral membrane or transmembrane proteins and are responsible for the non-covalent interactions of these proteins with membrane lipids. Here we report a profile Hidden Markov Model based method capable of detecting Membrane Binding Proteins (MBPs) from information encoded in their amino acid sequence, called MBPpred. The method identifies MBPs that contain one or more of the Membrane Binding Domains (MBDs) that have been described to date, and further classifies these proteins based on their position in respect to the membrane, either as peripheral or transmembrane. MBPpred is available online at http://bioinformatics.biol.uoa.gr/MBPpred. This method was applied in selected eukaryotic proteomes, in order to examine the characteristics they exhibit in various eukaryotic kingdoms and phylums.

INTRODUCTION Hereditary breast cancer is estimated to account for approximately 10% of all breast cancer cases. In addition, an estimated 15-20% of those affected by breast cancer have a positive family history. Despite the fact that BRCA1 and BRCA2 are the two most significant genes in hereditary breast cancer predisposition, twenty years of analysis has highlighted the fact, that mutations in these two highly penetrant genes, are only present in approximately 20% of high risk families. Other genes, mutations in which are associated with high risk of breast cancer, were identified because of the strong association with familial cancer syndromes, in which breast cancer is one of the defining components. Technological advances in molecular biology and especially DNA sequencing, commonly designated as “Next Generation Sequencing – NGS” have aided in the concentrated efforts to identify new genes responsible for the missing heritability, allowing the application of this knowledge in the diagnostic setting. AIM The aim of this study was to investigate the extent and nature of mutations in 26 genes implicated in hereditary cancer predisposition in families of Romanian descent. MATERIALS & METHODS In total, 297 Romanian families have been analyzed by our group in the past three years. Genomic DNA was enriched for targeted regions of 26 genes involved in hereditary predisposition to cancer (ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM (only intron 8, exon 9 and 3'UTR), FAM175A, MEN1, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, XRCC2). Sequencing was carried out using the Illumina NGS technology. Reads were aligned to the reference sequence (GRCh38), and sequence changes were identified and interpreted in the context of a single clinically relevant transcript. The presence of large genomic rearrangements was investigated by use of MLPA. All clinically significant observations were confirmed by orthogonal technologies. RESULTS In total, a pathogenic mutation was identified in 79 of the 297 families (26.6%) analyzed. Clinically significant mutations were identified in 17 of the genes included in the panel. The most commonly mutated genes in the Romanian population were BRCA1 and BRCA2, accounting for 50% of the mutations identified, followed by PALB2 (12%), CHEK2 (9.4%) and ATM, NBN and RAD50 which accounted for 3.5% of the mutations each. Of note is that 7 of the 79 affected families (8.8%) carried clinically significant mutations in two different genes. CONCLUSIONS Our results support the clinical significance of analysis of a panel of genes involved in hereditary cancer predisposition. In this series of patients, analysis of this panel allowed for the identification of 14% additional pathogenic variants. This is especially true in those cases where more than one pathogenic variant was identified. Citation Format: Tsoulos N, Apessos A, Agiannitopoulos K, Pepe G, Tsaousis G, Kambouri S, Eniu DT, Ungureanu A, Banu E, Ciule L, Blidaru A, Chiorean A, Stanculeanu DL, Mateescu D, Nasioulas G. Analysis of hereditary cancer syndromes by use of a panel of genes: More answers than questions [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-03-03.

e23193 Background: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and a tumor with broad spectrum of targeted therapies already available or in clinical trials. Thus, molecular characterization of the tumor using the Next Generation Sequencing (NGS) technology, has become a key tool for NSCLC patients’ treatment decision and clinical management. Methods: The performance of a custom 23 gene multiplex amplification hot spot panel, based on Ion AmpliSeq Technology, was evaluated for the analysis of tumor DNA extracted from FFPE (Formalin Fixed Parraffin Embedded) tissue. Furthermore the Ion AmpliSeq™ RNA Fusion Lung Cancer Research Panel was used for fusion RNA transcript analysis. Tumors’ mutation spectrum was determined in a cohort of 502 patients with NSCLC using the aforementioned targeted gene panels. Results: The panel used for tumor DNA analysis in this study exhibit high rates (100%) of sensitivity, specificity and reproducibility at a mutation frequency of 3%. At least one DNA mutation was detected in 374 patients (74.5%) and an RNA fusion was identified in 16 patients, (3.2%). In total, alterations in a cancer driver gene were identified (including point mutations, gene rearrangements and MET amplifications) in 77.6% of the tumors tested. Among the NSCLC patients, 13.5% (68/502) presented a mutation in a gene with approved targeted therapy (EGFR, ALK ROS1) and 9.4% had an alteration in a gene related to emerging targeted therapies according the NCCN guidelines. These alterations include ERBB2, BRAF and MET mutations, MET amplification and RET rearrangements. The remaining 51.6% of the patients had a mutation in a gene that could be related to an off label therapy or give them access to a clinical trial. Conclusions: Thus the NGS panel validated is a reliable approach of clinical applicability for tumor molecular profile detection in NSCLC patients.

A major part of membrane function is conducted by proteins, both integral and peripheral. Peripheral membrane proteins temporarily adhere to biological membranes, either to the lipid bilayer or to integral membrane proteins with non-covalent interactions. The aim of this study was to construct and analyze the interactions of the human plasma membrane peripheral proteins (peripherome hereinafter). For this purpose, we collected a dataset of peripheral proteins of the human plasma membrane. We also collected a dataset of experimentally verified interactions for these proteins. The interaction network created from this dataset has been visualized using Cytoscape. We grouped the proteins based on their subcellular location and clustered them using the MCL algorithm in order to detect functional modules. Moreover, functional and graph theory based analyses have been performed to assess biological features of the network. Interaction data with drug molecules show that ~10% of peripheral membrane proteins are targets for approved drugs, suggesting their potential implications in disease. In conclusion, we reveal novel features and properties regarding the protein-protein interaction network created by peripheral proteins of the human plasma membrane., Comment: 39 pages, 5 figures, 3 supplement figures, under review in BMRI

Molecular Recognition Features (MoRFs) are defined as short, intrinsically disordered regions in proteins that undergo disorder-to-order transition upon binding to their partners. As their name suggests, they are implicated in molecular recognition, which serves as the initial step for protein-protein interactions. Membrane proteins constitute approximately 30% of fully sequenced proteomes and are responsible for a wide variety of cellular functions. The aim of the current study was to identify and analyze MoRFs in membrane proteins. Two datasets of MoRFs, transmembrane and peripheral membrane protein MoRFs, were constructed from the Protein Data Bank, and sequence, structural and functional analysis was performed. Characterization of our datasets revealed their unique compositional biases and membrane protein MoRFs were categorized depending on their secondary structure after the interaction with their partners. Moreover, the position of transmembrane protein MoRFs in relation with the protein's topology was determined. Further studies were focused on functional analyses of MoRF-containing proteins and MoRFs' partners, associating them with protein binding, regulation and cell signaling, indicating half of them as putative hubs in protein-protein interaction networks. In conclusion, we provide insights into the disorder-based protein-protein interactions involving membrane proteins.

Motivations. During the past few years there has been a growing interest in the field of intrinsically disordered proteins-related research. Intrinsically disordered proteins (IDPs) possess no rigid 3D structure under physiological conditions, yet they are functionally active. A protein may be fully or partly disordered, containing long or short intrinsically disordered regions (IDRs). Molecular Recognition Features (MoRFs), known also as Molecular Recognition Elements (MoREs), are defined as short regions that undergo disorder-to-order transition upon binding to their partners. As their name suggests, they are considered to be implicated in molecular recognition, which serves as the initial step for protein-protein interactions. Membrane proteins comprise approximately 30% of fully sequenced proteomes and they are responsible for a wide variety of cellular functions, including cell signalling. The aim of the current study was to identify and analyse MoRFs in membrane proteins. Methods. A dataset of putative MoRFs was constructed from the Protein Data Bank, selecting membrane protein fragments between 10 and 70 residues, which interact with proteins longer than 100 residues. The assumption was made that such short aminoacid sequences would be less likely to form a rigid 3D structure prior to interaction. The initial dataset was further filtered for ambiguous information and a non-redundant dataset was created applying length-dependent thresholds. Subsequently, sequence, structural and functional analysis of the membrane MoRF non-redundant dataset was conducted. Results. Initialy, we sought to characterize our dataset and assess membrane MoRF associations with intrinsic disorder. Approximately half of the membrane MoRFs are short, between 10 and 20 residues. In addition, membrane MoRFs' aminoacid composition was found to differ not only from that of a typical IDR, as expected, but from globular MoRFs' aminoacid preferences as well. A structure-based criterion, evaluating per-residue surface and interface areas, supported the idea that membrane MoRFs are intrinsically disordered when isolated, and undergo a disorder-to-order transition upon binding. Missing density residues, often associated with disorder, were also assessed and were found to comprise, along with irregular residues, more than half of membrane MoRFs' secondary structure. Membrane MoRFs were categorized as alpha, beta, irregular and complex, depending on their secondary structure after the interaction with their partners. Further studies were focused on MoRF-containing proteins and revealed that the vast majority are eukaryotic single-spanning transmembrane proteins. Moreover, the position of MoRFs in relation to the protein's topology was determined. Finally, functional analyses of MoRF-containing proteins and MoRF-binding partners are currently under way. In conclusion, our goal is to provide insight into potential disorder-based protein-protein interactions involving membrane proteins. A comparison between membrane and globular MoRFs will allow us to determine if they are likewise implicated in molecular recognition procedures and whether a similar mechanism is involved. In the long term, the above information will facilitate identification, and possibly prediction, of membrane MoRFs.