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BACKGROUND: Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients. METHODS: Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants. RESULTS: Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA's. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified. CONCLUSIONS: This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.

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The exon junction complex (EJC) plays key roles throughout the lifespan of RNA and is particularly relevant in the nervous system. We investigated the roles of two EJC members, the paralogs MAGOH and MAGOHB, with respect to brain tumour development. High MAGOH/MAGOHB expression was observed in 14 tumour types; glioblastoma (GBM) showed the greatest difference compared to normal tissue. Increased MAGOH/MAGOHB expression was associated with poor prognosis in glioma patients, while knockdown of MAGOH/MAGOHB affected different cancer phenotypes. Reduced MAGOH/MAGOHB expression in GBM cells caused alterations in the splicing profile, including re-splicing and skipping of multiple exons. The binding profiles of EJC proteins indicated that exons affected by MAGOH/MAGOHB knockdown accumulated fewer complexes on average, providing a possible explanation for their sensitivity to MAGOH/MAGOHB knockdown. Transcripts (genes) showing alterations in the splicing profile are mainly implicated in cell division, cell cycle, splicing, and translation. We propose that high MAGOH/MAGOHB levels are required to safeguard the splicing of genes in high demand in scenarios requiring increased cell proliferation (brain development and GBM growth), ensuring efficient cell division, cell cycle regulation, and gene expression (splicing and translation). Since differentiated neuronal cells do not require increased MAGOH/MAGOHB expression, targeting these paralogs is a potential option for treating GBM.

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Bladder cancer (BC) is the most common neoplasm of the urinary tract, which originates in the epithelium that covers the inner surface of the bladder. The molecular BC profile has led to the development of different classifications of non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). However, the genomic BC landscape profile of the Mexican population, including NMIBC and MIBC, is unknown. In this study, we aimed to identify somatic single nucleotide variants (SNVs) and copy number variations (CNVs) in Mexican patients with BC and their associations with clinical and pathological characteristics. We retrospectively evaluated 37 patients treated between 2012 and 2021 at the National Cancer Institute-Mexico (INCan). DNA samples were obtained from paraffin-embedded tumor tissues and exome sequenced. Strelka2 and Lancet packages were used to identify SNVs and insertions or deletions. FACETS was used to determine CNVs. We found a high frequency of mutations in TP53 and KMT2D, gains in 11q15.5 and 19p13.11-q12, and losses in 7q11.23. STAG2 mutations and 1q11.23 deletions were also associated with NMIBC and low histologic grade.

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The Hispanic population, compared with other ethnic groups, presents a more aggressive gastric cancer phenotype with higher frequency of diffuse-type gastric adenocarcinoma (GA); this could be related to the mutational landscape of GA in these patients. Using whole-exome sequencing, we sought to present the mutational landscape of GA from 50 Mexican patients who were treated at The Instituto Nacional de Cancerología from 2019 to 2020. We performed a comprehensive statistical analysis to explore the relationship of the genomic variants and clinical data such as tumor histology and presence of signet-ring cell, H. pylori, and EBV. We describe a potentially different mutational landscape between diffuse and intestinal GA in Mexican patients. Patients with intestinal-type GA tended to present a higher frequency of NOTCH1 mutations, copy number gains in cytobands 13.14, 10q23.33, and 12q25.1, and copy number losses in cytobands 7p12, 14q24.2, and 11q13.1; whereas patients with diffuse-type GA tended to present a high frequency of CDH1 mutations and CNV gains in cytobands 20q13.33 and 22q11.21. This is the first description of a mutational landscape of GA in Mexican patients to better understand tumorigenesis in Hispanic patients and lay the groundwork for discovering potential biomarkers and therapeutic targets.

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Glioblastoma (GBM) is the most aggressive and common brain cancer in adults with the lowest life expectancy. The current neuro-oncology practice has incorporated genes involved in key molecular events that drive GBM tumorigenesis as biomarkers to guide diagnosis and design treatment. This study summarizes findings describing the significant heterogeneity of GBM at the transcriptional and genomic levels, emphasizing 18 driver genes with clinical relevance. A pattern was identified fitting the stem cell model for GBM ontogenesis, with an upregulation profile for MGMT and downregulation for ATRX, H3F3A, TP53 and EGFR in the mesenchymal subtype. We also detected overexpression of EGFR, NES, VIM and TP53 in the classical subtype and of MKi67 and OLIG2 genes in the proneural subtype. Furthermore, we found a combination of the four biomarkers EGFR, NES, OLIG2 and VIM with a remarkable differential expression pattern which confers them a strong potential to determine the GBM molecular subtype. A unique distribution of somatic mutations was found for the young and adult population, particularly for genes related to DNA repair and chromatin remodelling, highlighting ATRX, MGMT and IDH1. Our results also revealed that highly lesioned genes undergo differential regulation with particular biological pathways for young patients. This multi-omic analysis will help delineate future strategies related to the use of these molecular markers for clinical decision-making in the medical routine.

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Risk stratification by genomic signatures has been shown to improve prognostication and guide treatment decisions among patients with hormone-sensitive breast cancer. However, their role in young women has not been fully elucidated. In this review, a systematic search was conducted for published articles and abstracts from major congresses that evaluated the use of genomic signatures in young breast cancer patients. A total of 71 studies were analyzed, including 561,188 patients of whom 27,748 (4.9%) were young. Women aged ≤40 years were subjected to genomic testing at a similar rate to older women but had a higher proportion of intermediate- to high-risk tumors when classified by EndoPredict (p = 0.04), MammaPrint (p < 0.01), and Oncotype DX (p < 0.01). In young women with low genomic risk, 6-year distant recurrence-free survival was 94%, while 5-year overall survival was nearly 100%. Nonetheless, young patients classified as low-risk had a higher tendency to receive chemotherapy compared to their older counterparts. In conclusion, genomic tests are useful tools for identifying young patients in whom chemotherapy omission is appropriate.

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Patients with triple-negative breast cancer (TNBC) have a poor prognosis, partly because of the absence of targeted therapies. Recognition of the key role of immune responses against cancer has allowed the advent of immunotherapy, focused on the inhibition of negative immune checkpoints, such as CTLA-4. CTLA-4 is also expressed in some cancer cells, but its activity in tumor cells is not completely understood. Thus, the aim of the present work was to determine the biological landscape and functions of CTLA-4 expressed in TNBC cells through preclinical and in silico analysis. Exploration of CTLA-4 by immunohistochemistry in 50 TNBC tumors revealed membrane and cytoplasmic expression at different intensities. Preclinical experiments, using TNBC cell lines, showed that stimulation of CTLA-4 with CD80 enhances activation of the ERK1/2 signaling pathway, while CTLA-4 blockade by Ipilimumab induces the activation of AKT and reduces cell proliferation in vitro. We then developed an analytic pipeline to define the effects of CTLA-4 in available public data that allowed us to identify four distinct tumor clusters associated with CTLA-4 activation, which are characterized by enrichment of distinctive pathways associated with cell adhesion, MAPK signaling, TGF-ß, VEGF, TNF-α, drug metabolism, ion and amino acid transport, and KRAS signaling, among others. In addition, blockade of CTLA-4 induced increased secretion of IL-2 by tumor cells, suggesting that the receptor regulates cellular functions that may impact the immune microenvironment. This is relevant because a deep characterization of immune infiltrate, conducted using public data to estimate the abundancies of immune-cell types, showed that CTLA-4-activated-like tumors present a conditional immune state similar to an escape phenotype exploited by cancer cells. Finally, by interrogating transcriptional predictors of immunotherapy response, we defined that CTLA-4 activation correlates with high immune scores related to good clinical predicted responses to anti-CTLA-4 therapy. This work sheds new light on the roles of activated CLTA-4 in the tumor compartment and suggests an important interplay between tumor CLTA-4-activated portraits and immune-infiltrating cell populations.

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Cancer is one of the leading causes of mortality worldwide. Breast cancer is the most frequent cancer in women, and in recent years it has become a serious public health problem in Colombia. The development of large-scale omic techniques allows simultaneous analysis of all active genes in tumor cells versus normal cells, providing new ways to discover the drivers of malignant transformations. Whole exome sequencing (WES) was obtained to provide a deep view of the mutational genomic profile in a set of cancer samples from Southwest Colombian women. WES was performed on 52 tumor samples from patients diagnosed with invasive breast cancer, which in most cases (33/52) were ductal luminal breast carcinomas (IDC-LM-BRCA). Global variant call was calculated, and six different algorithms were applied to filter out false positives and identify pathogenic variants. To compare and expand the somatic tumor variants found in the Colombian cohort, exome mutations and genome-wide expression alterations were detected in a larger set of tumor samples of the same breast cancer subtype from TCGA (that included DNA-seq and RNA-seq data). Genes with significant changes in both the mutational and expression profiles were identified, providing a set of genes and mutations associated with the etiology of ductal luminal breast cancer. This set included 19 single mutations identified as tumor driver mutations in 17 genes. Some of the genes (ATM, ERBB3, ESR1, TP53) are well-known cancer genes, while others (CBLB, PRPF8) presented driver mutations that had not been reported before. In the case of the CBLB gene, several mutations were identified in TCGA IDC-LM-BRCA samples associated with overexpression of this gene and repression of tumor suppressive activity of TGF-ß pathway.

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BACKGROUND: Cachexia is a multifactorial syndrome highly associated with specific tumour types, but the causes of variation in cachexia prevalence and severity are unknown. While circulating plasma mediators (soluble cachectic factors) derived from tumours have been implicated with the pathogenesis of the syndrome, these associations were generally based on plasma concentration rather than tissue-specific gene expression levels. Here, we hypothesized that tumour gene expression profiling of cachexia-inducing factors (CIFs) in human cancers with different prevalence of cachexia could reveal potential cancer-specific cachexia mediators and biomarkers of clinical outcome. METHODS: First, we combined uniformly processed RNA sequencing data from The Cancer Genome Atlas and Genotype-Tissue Expression databases to characterize the expression profile of secretome genes in 12 cancer types (4651 samples) compared with their matched normal tissues (2737 samples). We systematically investigated the transcriptomic data to assess the tumour expression profile of 25 known CIFs and their predictive values for patient survival. We used the Xena Functional Genomics tool to analyse the gene expression of CIFs according to neoplastic cellularity in pancreatic adenocarcinoma, which is known to present the highest prevalence of cachexia. RESULTS: A comprehensive characterization of the expression profiling of secreted genes in different human cancers revealed pathways and mediators with a potential role in cachexia within the tumour microenvironment. Cytokine-related and chemokine-related pathways were enriched in tumour types frequently associated with the syndrome. CIFs presented a tumour-specific expression profile, in which the number of upregulated genes was correlated with the cachexia prevalence (r2 : 0.80; P value: 0.002) and weight loss (r2 : 0.81; P value: 0.002). The distinct gene expression profile, according to tumour type, was significantly associated with prognosis (P value ≤ 1.96 E-06). In pancreatic adenocarcinoma, the upregulated CIF genes were associated with tumours presenting low neoplastic cellularity and high leucocyte fraction and not with tumour grade. CONCLUSIONS: Our results present a biological dimension of tumour-secreted elements that are potentially useful to explain why specific cancer types are more likely to develop cachexia. The tumour-specific profile of CIFs may help the future development of better targeted therapies to treat cancer types highly associated with the syndrome.

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BACKGROUND: Next generation sequencing instruments are providing new opportunities for comprehensive analyses of cancer genomes. The increasing availability of tumor data allows to research the complexity of cancer disease with machine learning methods. The large available repositories of high dimensional tumor samples characterised with germline and somatic mutation data requires advance computational modelling for data interpretation. In this work, we propose to analyze this complex data with neural network learning, a methodology that made impressive advances in image and natural language processing. RESULTS: Here we present a tumor mutation profile analysis pipeline based on an autoencoder model, which is used to discover better representations of lower dimensionality from large somatic mutation data of 40 different tumor types and subtypes. Kernel learning with hierarchical cluster analysis are used to assess the quality of the learned somatic mutation embedding, on which support vector machine models are used to accurately classify tumor subtypes. CONCLUSIONS: The learned latent space maps the original samples in a much lower dimension while keeping the biological signals from the original tumor samples. This pipeline and the resulting embedding allows an easier exploration of the heterogeneity within and across tumor types and to perform an accurate classification of tumor samples in the pan-cancer somatic mutation landscape.

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OBJECTIVE: To review the state-of-the-art in relation to the current information on squamous cell lung cancer (SCLC). We describe the genetic anomalies reported, their effect, and finally the most promising therapeutic agents. MATERIALS AND METHODS: We reviewed published articles in peer-reviewed journals as well as current treatment guidelines from local and international resources. RESULTS: SCLC represents a smaller proportion of the global burden of disease for lung cancer compared to its more frequent presentation, the adenocarcinoma. However, more than 400 000 cases are reported annually, a substantial population for whom therapeutic options are scarce and with limited efficacy. Several groups have been given the task of elucidating the mechanisms that lead to the development of SCLC, including molecular anomalies that can be used as targets for drug design. CONCLUSIONS: There are potential therapeutic targets for SCLC, which must be studied in clinical trials for validation.

OBJETIVO: Revisar el estado del arte en relación con la información actual sobre el cáncer de pulmón de células escamosas (CPCE) y describir las anomalías genéticas reportadas, su efecto y los agentes terapéuticos más prometedores. MATERIAL Y MÉTODOS: Se realizó una revisión de artículos publicados en revistas indizadas, así como las guías de tratamiento publicadas por instancias locales e internacionales. RESULTADOS: El CPCE representa una proporción menor de la carga mundial de la enfermedad por cáncer pulmonar en comparación con su presentación más frecuente, el adenocarcinoma. Sin embargo, más de 400 000 casos son reportados anualmente, una población sustancial para quienes las opciones terapéuticas son escasas y con una eficacia limitada. Diversos grupos se han dado a la tarea de elucidar los mecanismos que conllevan al desarrollo del CPCE, incluyendo anomalías moleculares que puedan servir como blancos para el diseño de fármacos. CONCLUSIONES: Existen blancos terapéuticos potenciales para el CPCE que deben ser estudiados en ensayos clínicos para ser validados.

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The mechanisms by which patients with RUNX1 familial platelet disorder with propensity to myeloid malignancies (FPDMM) develop myeloid malignancies (MM) are not fully understood. We report the results of targeted next-generation sequencing on three patients with RUNX1 FPDMM who developed acute myeloid leukaemia or myelodysplastic syndromes (AML/MDS). DNA samples were collected from bone marrow, peripheral blood and buccal swabs at different time points. One patient had clonal haematopoiesis, represented by an SRSF2 p.P95R variant, prior to his AML diagnosis, when he developed an additional NRAS p.G12D variant. His sister presented to us with MDS, with a TET2 p.S471fs and identical NRAS p.G12D variant. The third patient, from another family, had an additional RUNX1 p.R204X and an NFE2 p.Q139fs variant at AML diagnosis. This constitutes the first report of NFE2 variants in AML without extramedullary disease and NRAS variants in AML/MDS in the setting of FPDMM. A systematic review of the literature including our findings distinguishes two genetic landscapes at AML transformation from FPDMM characterized by either the presence or absence of somatic abnormalities in RUNX1 with or without variants in genes usually associated with MM. Whether clonal haematopoiesis precedes transformation only in patients without somatic abnormalities in RUNX1 needs further confirmation.

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The relationship between anti-tumoral immunity and cancer progression is complex. Recently, immune editing has emerged as a model to explain the interplay between the immune system and the selection of genetic alterations in cancer. In this model, the immune system selects cancer cells that grow as these are fit to escape immune surveillance during tumor development. Gliomas and glioblastoma, the most aggressive and most common of all primary malignant brain tumors are genetically heterogeneous, are relatively less antigenic, and are less responsive to immunotherapy than other cancers. In this review, we provide an overview of the relationship between glioma´s immune suppressive features, anti-tumoral immunity and cancer genomics. In this context, we provide a critical discussion of evidence suggestive of immune editing in this disease and discuss possible alternative explanations for these findings.

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BACKGROUND: Human cancer cell lines are valuable models for anti-cancer drug development. Although all cancer cells share common biological features, each cancer cell line has unique genotypic/ phenotypic characteristics that affect drug response. Thus, the information obtained with a specific cancer cell line cannot be easily extrapolated to other cancer cells. Consequently, cell line selection during experimental design is critical for providing proper and clinically relevant structure-activity analysis. METHODS: Herein, we critically review the use of cancer cell lines as tools for activity analysis by comparing two different scenarios: i) the use of multiple cancer cell lines, with the NCI-60 Program as the most representative example; and, ii) the selection of a single cell line with specific biological characteristics that match the rationale of compound design. RESULTS: Considering that most laboratories evaluate the activity of new compounds using few cell lines, we provide a systematic strategy for selection based on the expression levels and genetic status of the target and the effectiveness of target inhibition or silencing. We exemplify the use of public databases for data retrieval and analysis as well as the critical comparison of such information with published results. CONCLUSION: This approach refines cell line selection, avoiding the perpetuation of published poor selection and enhancing the relevance of the results.

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