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A person’s signature is merely a handwritten sign that closely resembles his/her name, frequently stylized and distinctive, and that expresses the person’s identity, intent, and consent. Two types of verifications are present. They are online signature verification and offline signature verification. Generally, Offline Signature verification is less efficient and slower process compare to online verification when come to the situation having larger number of documents and files to verify with in less time. Over the years, many researchers have developed so many methods for signature verifications to help the people or organizations to find whether the signature of a particular person is forged or genuine. To overcome this problems; In this paper we introduced a simple method to improve the verification of the signature in Image Processing using Convolution Neural Networks(CNN). Signature Verification it is used to authenticate various kinds of documents, including cheques, draughts, certificates, approvals, letters, and other legal ones, such verification is crucial for preventing document forgery and falsification. Previously, to verify a signature, it was manually checked against copies of real signatures. This straightforward approach might not be sufficient given that forgery and signature fraud techniques are becoming more sophisticated as a result of improving technology.

Castration-resistant prostate cancer is a heterogeneous disease with variable phenotypes commonly observed in later stages of the disease. These include cases that retain expression of luminal markers and those that lose hormone dependence and acquire neuroendocrine features. While there are distinct transcriptomic and epigenomic differences between castration-resistant adenocarcinoma and neuroendocrine prostate cancer, the extent of overlap and degree of diversity across tumor metastases in individual patients has not been fully characterized. Here we perform combined DNA methylation, RNA-sequencing, H3K27ac, and H3K27me3 profiling across metastatic lesions from patients with CRPC/NEPC. Integrative analyses identify DNA methylation-driven gene links based on location (H3K27ac, H3K27me3, promoters, gene bodies) pointing to mechanisms underlying dysregulation of genes involved in tumor lineage (ASCL1, AR ) and therapeutic targets (PSMA, DLL3, STEAP1, B7-H3). Overall, these data highlight how integration of DNA methylation with RNA-sequencing and histone marks can inform intraindividual epigenetic heterogeneity and identify putative mechanisms driving transcriptional reprogramming in castration-resistant prostate cancer. The epigenetic mechanisms underlying phenotypic diversity across different metastatic sites in castration-resistant prostate cancer (CRPC) remain to be characterised. Here, multi-omic profiling across metastatic lesions identifies regulatory networks driving tumour lineage programs and potential therapeutic targets.

The molecular characteristics of metastatic upper tract urothelial carcinoma (UTUC) are not well understood, and there is a lack of knowledge regarding the genomic and transcriptomic differences between primary and metastatic UTUC. To address these gaps, we integrate whole-exome sequencing, RNA sequencing, and Imaging Mass Cytometry using lanthanide metal-conjugated antibodies of 44 tumor samples from 28 patients with high-grade primary and metastatic UTUC. We perform a spatially-resolved single-cell analysis of cancer, immune, and stromal cells to understand the evolution of primary to metastatic UTUC. We discover that actionable genomic alterations are frequently discordant between primary and metastatic UTUC tumors in the same patient. In contrast, molecular subtype membership and immune depletion signature are stable across primary and matched metastatic UTUC. Molecular and immune subtypes are consistent between bulk RNA-sequencing and mass cytometry of protein markers from 340,798 single cells. Molecular subtypes at the single-cell level are highly conserved between primary and metastatic UTUC tumors within the same patient. Detailed molecular studies are required to understand the differences between primary and metastatic upper tract urothelial carcinoma (UTUC). Here, the authors use genomics, transcriptomics and imaging mass cytometry to characterise the molecular profiles of primary and metastatic UTUC, and find that molecular subtypes remain highly conserved.

Neuroendocrine prostate cancer is an aggressive variant of prostate cancer that may arise de novo or develop from pre-existing prostate adenocarcinoma as a mechanism of treatment resistance. The combined loss of tumor suppressors RB1, TP53, and PTEN are frequent in NEPC but also present in a subset of prostate adenocarcinomas. Most clinical and preclinical studies support a trans-differentiation process, whereby NEPC arises clonally from a prostate adenocarcinoma precursor during the course of treatment resistance. Here we highlight a case of NEPC with significant intra-patient heterogeneity observed across metastases. We further demonstrate how single-cell genomic analysis of circulating tumor cells combined with a phenotypic evaluation of cellular diversity can be considered as a window into tumor heterogeneity in patients with advanced prostate cancer.

Background Accurate human epidermal growth factor 2 (HER2) assessment is critical for guiding breast cancer (BC) treatment. Circulating tumor cells (CTCs), which detach from the primary or secondary tumors and circulate through the bloodstream, can colonize distant sites to form metastases. Previous studies have demonstrated the clinical validity of CTCs as prognostic biomarkers in metastatic breast cancer (mBC). Liquid biopsy testing offers a non-invasive alternative for real-time evaluation of HER2 expression on CTCs, overcoming limitations of repeated histological sampling. Methods This study employed a pipeline combining EpCAM-independent enrichment with Parsortix ® and immunofluorescence (IF)-based HER2 characterization to assess HER2 expression in patient-derived CTCs from sixteen patients with mBC and compared it to the FDA-approved CellSearch ® system and to the HER2 tissue status. CTC detection rates, median CTC counts per 7.5 mL blood, and the fraction of HER2-positive CTCs per sample were determined, and CTC versus tissue status was compared to assess concordance. Results The two methods had a strong positive correlation in CTC counts, with the label-free workflow showing a higher CTC detection (100% versus 77% samples with ≥ 1 CTC). Median total CTC counts per 7.5 mL blood were 16.5 (range 3–65) for Parsortix ® and 3 (range 1–245) for CellSearch ® . Despite a different HER2-positive CTC detection rate (38% versus 11% using Parsortix ® and CellSearch ® , respectively), both methods showed concordance with the tissue, with the distribution of HER2-positive CTCs reflecting the HER2 status of the biopsy. Patients with HER2-positive mBC showed a higher proportion of HER2-positive CTCs compared to patients with HER2-negative tissue both with Parsortix (55% versus 33%) and with CellSearch (61% versus 1%). No differences in HER2-positive CTC distribution were observed between patients with HER2-low and HER2-zero tumors. Conclusion These results support the clinical utility of HER2 assessment on CTCs with both workflows and highlight the potential diagnostic value of label-free CTC enrichment combined with HER2 quantification. Further studies in larger cohorts should be conducted to validate our findings and investigate the clinical relevance of HER2-positive CTCs detected with the developed pipeline, particularly in the context of anti-HER2 therapies.

The availability of fresh frozen (FF) tissue is a barrier for implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. We performed transcriptomic analysis of 32 FFPE tumor samples from 11 patients using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to the TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. The Spearman’s correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72–0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable gene transcripts, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen’s k = 0.7, p < 0.01). The Agilent and IDT assays detected all the clinically relevant fusions that were initially identified in FF-TruSeq. All FFPE exome capture-based methods had comparable performance and concordance with FF-TruSeq. Our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

Background Homologous recombination deficiency (HRD) impacts cancer treatment strategies, particularly effective utilization of PARP inhibitors. However, the variability of different HRD assays has hampered the selection of oncology patients who may benefit from these therapies. Our study aims to use the whole genome landscape to better define HRD in a pan-cancer cohort. Methods We employed a whole genome sequencing HRD classifier that includes genome-wide signatures associated with HRD to analyze 580 tumor/normal paired samples. The HRD phenotype was correlated with genomic variants in BRCA1/2 and other homologous recombination repair genes. Results In this paper we show that the HRD phenotype is identified in various cancers including breast (21%), pancreaticobiliary (20%), gynecological (17%), prostate (9%), upper gastrointestinal (GI) (2%), and other cancers (1%). HRD cases are not confined to BRCA1/2 mutations; 24% of HRD cases are BRCA1/2 wild-type. A diverse range of gene alterations involved in HRD are elucidated, including biallelic mutations in FANCF, XRCC2 , and FANCC , and deleterious structural variants. In a subset of cases, the whole genome sequencing-based classifier offers more insights and a better correlation to treatment response when compared to other assays. Conclusions Although HRD is a biomarker used to determine which cancer patients would benefit from PARP inhibitors, a lack of harmonization of tests to determine HRD status makes it challenging to interpret their results. Our study highlights the use of comprehensive whole genome sequencing analysis to better predict HRD and elucidates genomic mechanisms associated with this phenotype. Plain language summary Homologous recombination deficiency is a condition in which a cancer cell cannot repair certain types of DNA damage. It causes genetic instability and is often due to changes in parts of the DNA called genes, such as BRCA1 and BRCA2 . Cancers with this deficiency can be more readily killed by certain drugs that prevent DNA repair. Some of these drugs are approved for the treatment of several types of cancer, including ovarian, breast, pancreatic, and prostate cancers. To better identify tumors with this deficiency, we characterize the whole genome of cancer samples. We find that a comprehensive analysis of the entire genome improves the detection of homologous recombination deficiency. This type of analysis may provide a more accurate way to guide treatment decisions for people with cancer. Assaad, Hadi and Levine et al. develop a whole-genome sequencing classifier to improve the detection of homologous recombination deficiency (HRD) across a pan cancer cohort. The classifier detects HRD beyond BRCA1/2 mutations, reveals HRD-related genomic events, and correlates with treatment response in a subset of patients.

Aggressive variant and androgen receptor (AR)-independent castration resistant prostate cancers (CRPC) represent the most significant diagnostic and therapeutic challenges in prostate cancer. This study examined a case of simultaneous progression of both adenocarcinoma and squamous tumors from the same common origin. Using whole-genome and transcriptome sequencing from 17 samples collected over >6 years, we established the clonal relationship of all samples, defined shared complex structural variants, and demonstrated both divergent and convergent evolution at AR . Squamous CRPC-associated circulating tumor DNA was identified at clinical progression prior to biopsy detection of any squamous differentiation. Dynamic changes in the detection rate of histology-specific clones in circulation reflected histology-specific sensitivity to treatment. This dataset serves as an illustration of non-neuroendocrine transdifferentiation and highlights the importance of serial sampling at progression in CRPC for the detection of emergent non-adenocarcinoma histologies with implications for the treatment of lineage plasticity and transdifferentiation in metastatic CRPC.

Advanced urothelial cancer is a frequently lethal disease characterized by marked genetic heterogeneity 1 . In this study, we investigated the evolution of genomic signatures caused by endogenous and external mutagenic processes and their interplay with complex structural variants (SVs). We superimposed mutational signatures and phylogenetic analyses of matched serial tumours from patients with urothelial cancer to define the evolutionary dynamics of these processes. We show that APOBEC3-induced mutations are clonal and early, whereas chemotherapy induces mutational bursts of hundreds of late subclonal mutations. Using a genome graph computational tool 2 , we observed frequent high copy-number circular amplicons characteristic of extrachromosomal DNA (ecDNA)-forming SVs. We characterized the distinct temporal patterns of APOBEC3-induced and chemotherapy-induced mutations within ecDNA-forming SVs, gaining new insights into the timing of these mutagenic processes relative to ecDNA biogenesis. We discovered that most CCND1 amplifications in urothelial cancer arise within circular ecDNA-forming SVs. ecDNA-forming SVs persisted and increased in complexity, incorporating additional DNA segments and contributing to the evolution of treatment resistance. Oxford Nanopore Technologies long-read whole-genome sequencing followed by de novo assembly mapped out CCND1 ecDNA structure. Experimental modelling of CCND1 ecDNA confirmed its role as a driver of treatment resistance. Our findings define fundamental mechanisms that drive urothelial cancer evolution and have important therapeutic implications. Whole-genome sequencing of matched serial tumours from patients identifies two key mutagenic factors (APOBEC3 and chemotherapy) and extrachromosomal DNA-forming structural variants that drive treatment resistance in urothelial cancer.