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The overall prognosis for colorectal cancer (CRC) remains challenging as the survival time varies widely, even in patients with the same stage of disease. Recent studies suggest prognostic relevance of the novel markers of systemic inflammation, the systemic immune-inflammation index (SII), and the systemic inflammation response index (SIRI). We conducted a comprehensive meta-analysis to assess the prognostic significance of the SII and the SIRI in CRC. We searched the relevant literature for observational studies, and random effects models were employed to conduct a statistical analysis using the metaanalysisonline.com platform. Pooled effect sizes were reported with hazard ratios (HRs) and corresponding 95% confidence intervals (CI). Data from 29 studies published between 2016 and 2024, comprising 10,091 participants, were included in our meta-analysis on SII. CRC patients with high SII levels had worse disease outcomes, which were associated with poor OS (HR: 1.75; 95% CI: 1.4-2.19) and poor PFS/DFS/RFS (HR: 1.25; 95% CI: 1.18-1.33). This increased risk of worse OS was present irrespective of the treatment strategy, sample size (<220 and ≥220), and cutoff used to define high and low SII (<550 and ≥550) groups. Based on data from five studies comprising 2362 participants, we found a strong association between the high SIRI and worse OS (HR: 2.65; 95% CI: 1.6-4.38) and DFS/RFS (HR: 2.04; 95% CI: 1.42-2.93). According to our results, both the SII and SIRI hold great promise as prognostic markers in CRC. Further validations are needed for their age- and stage-specific utility in the clinical routine.
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Neoplasias Colorretais , Inflamação , Humanos , Biomarcadores Tumorais , Neoplasias Colorretais/imunologia , Neoplasias Colorretais/mortalidade , Neoplasias Colorretais/diagnóstico , Inflamação/imunologia , PrognósticoRESUMO
Colorectal cancer (CRC) is a major global health concern and represents a significant public health challenge in Hungary, where it exhibits some of the highest morbidity and mortality rates in the European Union. The Mediterranean diet has been suggested to reduce the incidence of CRC, but comprehensive evidence from diverse study designs is needed to substantiate this effect. A systematic literature search was conducted in PubMed, ClinicalTrials.gov, CENTRAL, and the Web of Science to identify randomized controlled trials and human clinical trials from 2008 to 2024 to identify relevant studies. Statistical analysis was performed using the https://metaanalysisonline.com web application using a random effects model to estimate the pooled hazard rates (HRs). Forest plots, funnel plots, and Z-score plots were utilized to visualize results. We identified 15 clinical trials and 9 case-control studies, encompassing a total of 2,217,404 subjects. The pooled analysis indicated that adherence to the Mediterranean diet significantly reduced the prevalence of CRC (HR = 0.84, 95% CI = 0.78-0.91, p < 0.01). This protective effect was consistent across sexes, with HRs of 0.85 (95% CI = 0.75-0.97, p = 0.01) for males and 0.88 (95% CI = 0.79-0.99, p = 0.03) for females. Case-control studies specifically showed a substantial effect (HR = 0.51, 95% CI = 0.38-0.68, p < 0.01). Notable heterogeneity was observed across studies, yet the a priori information size was substantially below the cumulative sample size, ensuring sufficient data for reliable conclusions. The findings from this meta-analysis reinforce the protective role of the Mediterranean diet against CRC. The results of this meta-analysis will inform dietary interventions designed to mitigate CRC risk, which are conducted within the framework of the Semmelweis Study, an ongoing comprehensive cohort study at Semmelweis University, designed to explore the multifaceted causes of unhealthy aging in Hungary. These interventions aim to explore the practical application of Mediterranean dietary patterns in reducing CRC incidence among the Hungarian population.
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Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience of large-scale datasets including multiple levels of data, new bioinformatic tools are needed to transform this wealth of information into clinically useful decision-support tools. In this field, artificial intelligence (AI) technologies with their highly diverse applications are rapidly gaining ground. Machine learning methods, such as Bayesian networks, support vector machines, decision trees, random forests, gradient boosting, and K-nearest neighbors, including neural network models like deep learning, have proven valuable in predictive, prognostic, and diagnostic studies. Researchers have recently employed large language models to tackle new dimensions of problems. However, leveraging the opportunity to utilize AI in clinical settings will require surpassing significant obstacles-a major issue is the lack of use of the available reporting guidelines obstructing the reproducibility of published studies. In this review, we discuss the applications of AI methods and explore their benefits and limitations. We summarize the available guidelines for AI in healthcare and highlight the potential role and impact of AI models on future directions in cancer research.
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Acute myeloid leukemia (AML) is a heterogenous disease characterized by the clonal expansion of myeloid progenitor cells. Despite recent advancements in the treatment of AML, relapse still remains a significant challenge, necessitating the development of innovative therapies to eliminate minimal residual disease. One promising approach to address these unmet clinical needs is natural killer (NK) cell immunotherapy. To implement such treatments effectively, it is vital to comprehend how AML cells escape the NK-cell surveillance. Signal transducer and activator of transcription 3 (STAT3), a component of the Janus kinase (JAK)-STAT signaling pathway, is well-known for its role in driving immune evasion in various cancer types. Nevertheless, the specific function of STAT3 in AML cell escape from NK cells has not been deeply investigated. In this study, we unravel a novel role of STAT3 in sensitizing AML cells to NK-cell surveillance. We demonstrate that STAT3-deficient AML cell lines are inefficiently eliminated by NK cells. Mechanistically, AML cells lacking STAT3 fail to form an immune synapse as efficiently as their wild-type counterparts due to significantly reduced surface expression of intercellular adhesion molecule 1 (ICAM-1). The impaired killing of STAT3-deficient cells can be rescued by ICAM-1 overexpression proving its central role in the observed phenotype. Importantly, analysis of our AML patient cohort revealed a positive correlation between ICAM1 and STAT3 expression suggesting a predominant role of STAT3 in ICAM-1 regulation in this disease. In line, high ICAM1 expression correlates with better survival of AML patients underscoring the translational relevance of our findings. Taken together, our data unveil a novel role of STAT3 in preventing AML cells from escaping NK-cell surveillance and highlight the STAT3/ICAM-1 axis as a potential biomarker for NK-cell therapies in AML.
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Molécula 1 de Adesão Intercelular , Células Matadoras Naturais , Leucemia Mieloide Aguda , Fator de Transcrição STAT3 , Fator de Transcrição STAT3/metabolismo , Humanos , Leucemia Mieloide Aguda/imunologia , Células Matadoras Naturais/imunologia , Células Matadoras Naturais/metabolismo , Molécula 1 de Adesão Intercelular/metabolismo , Molécula 1 de Adesão Intercelular/genética , Vigilância Imunológica , Linhagem Celular Tumoral , Evasão Tumoral , Transdução de Sinais , Citotoxicidade ImunológicaRESUMO
Introduction: While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Methods: Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Results: Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Discussion: Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.
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N6-adenosine methylation (m6A) is critical for controlling cancer cell growth and tumorigenesis. However, the function and detailed mechanism of how m6A methyltransferases modulate m6A levels on specific targets remain unknown. In the current study, we identified significantly elevated levels of RBM15, an m6A writer, in basal-like breast cancer (BC) patients compared to nonbasal-like BC patients and linked this increase to worse clinical outcomes. Gene expression profiling revealed correlations between RBM15 and serine and glycine metabolic genes, including PHGDH, PSAT1, PSPH, and SHMT2. RBM15 influences m6A levels and, specifically, the m6A levels of serine and glycine metabolic genes via direct binding to target RNA. The effects of RBM15 on cell growth were largely dependent on serine and glycine metabolism. Thus, RBM15 coordinates cancer cell growth through altered serine and glycine metabolism, suggesting that RBM15 is a new therapeutic target in BC.
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Proliferação de Células , Regulação Neoplásica da Expressão Gênica , Glicina , Proteínas de Ligação a RNA , Serina , Neoplasias de Mama Triplo Negativas , Humanos , Serina/metabolismo , Glicina/metabolismo , Feminino , Proteínas de Ligação a RNA/metabolismo , Proteínas de Ligação a RNA/genética , Linhagem Celular Tumoral , Neoplasias de Mama Triplo Negativas/metabolismo , Neoplasias de Mama Triplo Negativas/genética , Neoplasias de Mama Triplo Negativas/patologia , Metilação , Adenosina/metabolismo , Adenosina/análogos & derivadosRESUMO
While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.
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The identification of targets that are expressed on the cell membrane is a main goal in cancer research. The Lymphocyte Antigen 6 Family Member G6D (LY6G6D) gene codes for a protein that is mainly present on the surface of colorectal cancer (CRC) cells. Therapeutic strategies against this protein like the development of T cell engagers (TCE) are currently in the early clinical stage. In the present work, we interrogated public genomic datasets including TCGA to evaluate the genomic and immunologic cell profile present in tumors with high expression of LY6G6D. We used data from TCGA, among others, and the Tumor Immune Estimation Resource (TIMER2.0) platform for immune cell estimations and Spearman correlation tests. LY6G6D expression was exclusively present in CRC, particularly in the microsatellite stable (MSS) subtype, and was associated with left-side tumors and the canonical genomic subgroup. Tumors with mutations of APC and p53 expressed elevated levels of LY6G6D. This protein was expressed in tumors with an inert immune microenvironment with an absence of immune cells and co-inhibitory molecules. In conclusion, we described clinical, genomic and immune-pathologic characteristics that can be used to optimize the clinical development of agents against this target. Future studies should be performed to confirm these findings and potentially explore the suggested clinical development options.
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Neoplasias Colorretais , Neoplasias Colorretais/imunologia , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Neoplasias Colorretais/metabolismo , Humanos , Microambiente Tumoral/imunologia , Microambiente Tumoral/genética , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo , Feminino , Masculino , Proteína da Polipose Adenomatosa do Colo/genética , Proteína da Polipose Adenomatosa do Colo/metabolismo , Regulação Neoplásica da Expressão Gênica , Mutação , Pessoa de Meia-Idade , Idoso , Biomarcadores Tumorais/genética , Proteínas Ligadas por GPI/genética , Proteínas Ligadas por GPI/metabolismo , Antígenos Ly/metabolismo , Antígenos Ly/genética , Antígenos B7/genética , Antígenos B7/metabolismoRESUMO
Signal transducer and activator of transcription 3 (STAT3) is frequently overexpressed in patients with acute myeloid leukemia (AML). STAT3 exists in two distinct alternatively spliced isoforms, the full-length isoform STAT3α and the C-terminally truncated isoform STAT3ß. While STAT3α is predominantly described as an oncogenic driver, STAT3ß has been suggested to act as a tumor suppressor. To elucidate the role of STAT3ß in AML, we established a mouse model of STAT3ß-deficient, MLL-AF9-driven AML. STAT3ß deficiency significantly shortened survival of leukemic mice confirming its role as a tumor suppressor. Furthermore, RNA sequencing revealed enhanced STAT1 expression and interferon (IFN) signaling upon loss of STAT3ß. Accordingly, STAT3ß-deficient leukemia cells displayed enhanced sensitivity to blockade of IFN signaling through both an IFNAR1 blocking antibody and the JAK1/2 inhibitor Ruxolitinib. Analysis of human AML patient samples confirmed that elevated expression of IFN-inducible genes correlated with poor overall survival and low STAT3ß expression. Together, our data corroborate the tumor suppressive role of STAT3ß in a mouse model in vivo. Moreover, they provide evidence that its tumor suppressive function is linked to repression of the STAT1-mediated IFN response. These findings suggest that the STAT3ß/α mRNA ratio is a significant prognostic marker in AML and holds crucial information for targeted treatment approaches. Patients displaying a low STAT3ß/α mRNA ratio and unfavorable prognosis could benefit from therapeutic interventions directed at STAT1/IFN signaling.
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Leucemia Mieloide Aguda , Fator de Transcrição STAT3 , Animais , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/patologia , Leucemia Mieloide Aguda/metabolismo , Humanos , Fator de Transcrição STAT3/metabolismo , Camundongos , Transdução de Sinais , Interferons/metabolismo , Fator de Transcrição STAT1/metabolismo , Fator de Transcrição STAT1/genética , Camundongos Endogâmicos C57BL , Receptor de Interferon alfa e beta/metabolismo , Receptor de Interferon alfa e beta/genética , Linhagem Celular Tumoral , Nitrilas , Pirazóis , PirimidinasRESUMO
Hyperthermia, the raising of tumor temperature (≥39°C), holds great promise as an adjuvant treatment for cancer therapy. This review focuses on 2 key aspects of hyperthermia: its molecular and cellular effects and its impact on the immune system. Hyperthermia has profound effects on critical biological processes. Increased temperatures inhibit DNA repair enzymes, making cancer cells more sensitive to chemotherapy and radiation. Elevated temperatures also induce cell cycle arrest and trigger apoptotic pathways. Furthermore, hyperthermia modifies the expression of heat shock proteins, which play vital roles in cancer therapy, including enhancing immune responses. Hyperthermic treatments also have a significant impact on the body's immune response against tumors, potentially improving the efficacy of immune checkpoint inhibitors. Mild systemic hyperthermia (39°C-41°C) mimics fever, activating immune cells and raising metabolic rates. Intense heat above 50°C can release tumor antigens, enhancing immune reactions. Using photothermal nanoparticles for targeted heating and drug delivery can also modulate the immune response. Hyperthermia emerges as a cost-effective and well-tolerated adjuvant therapy when integrated with immunotherapy. This comprehensive review serves as a valuable resource for the selection of patient-specific treatments and the guidance of future experimental studies.
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Hipertermia Induzida , Imunoterapia , Neoplasias , Animais , Humanos , Terapia Combinada/métodos , Sistemas de Liberação de Medicamentos/métodos , Hipertermia Induzida/métodos , Imunoterapia/métodos , Neoplasias/terapia , Neoplasias/imunologiaRESUMO
Regulatory T cells (Tregs) is a subtype of CD4+ T cells that produce an inhibitory action against effector cells. In the present work we interrogated genomic datasets to explore the transcriptomic profile of breast tumors with high expression of Tregs. Only 0.5% of the total transcriptome correlated with the presence of Tregs and only four transcripts, BIRC6, MAP3K2, USP4 and SMG1, were commonly shared among the different breast cancer subtypes. The combination of these genes predicted favorable outcome, and better prognosis in patients treated with checkpoint inhibitors. Twelve up-regulated genes coded for proteins expressed at the cell membrane that included functions related to neutrophil activation and regulation of macrophages. A positive association between MSR1 and CD80 with macrophages in basal-like tumors and between OLR1, ABCA1, ITGAV, CLEC5A and CD80 and macrophages in HER2 positive tumors was observed. Expression of some of the identified genes correlated with favorable outcome and response to checkpoint inhibitors: MSR1, CD80, OLR1, ABCA1, TMEM245, and ATP13A3 predicted outcome to anti PD(L)1 therapies, and MSR1, CD80, OLR1, ANO6, ABCA1, TMEM245, and ATP13A3 to anti CTLA4 therapies, including a subgroup of melanoma treated patients. In this article we provide evidence of genes strongly associated with the presence of Tregs that modulates the response to check point inhibitors.
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Neoplasias da Mama , Linfócitos T Reguladores , Transcriptoma , Humanos , Linfócitos T Reguladores/imunologia , Linfócitos T Reguladores/metabolismo , Linfócitos T Reguladores/efeitos dos fármacos , Feminino , Neoplasias da Mama/genética , Neoplasias da Mama/tratamento farmacológico , Inibidores de Checkpoint Imunológico/uso terapêutico , Inibidores de Checkpoint Imunológico/farmacologia , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Perfilação da Expressão Gênica , PrognósticoRESUMO
Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer (HDBC), potentially explaining ~40% of relapses. If other mechanisms underlie the evolution of HDBC under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CREs) to cancer evolution by focusing on 12 megabases of non-coding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of non-coding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies triggers the emergence of transient features which could ultimately be exploited to hinder the adaptive process.
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Identifying genes with prognostic significance that can act as biomarkers in solid tumors can help stratify patients and uncover novel therapy targets. Here, our goal was to expand our previous ranking analysis of survival-associated genes in various solid tumors to include colon cancer specimens with available transcriptomic and clinical data. A Gene Expression Omnibus search was performed to identify available datasets with clinical data and raw gene expression measurements. A combined database was set up and integrated into our Kaplan-Meier plotter, making it possible to identify genes with expression changes linked to altered survival. As a demonstration of the utility of the platform, the most powerful genes linked to overall survival in colon cancer were identified using uni- and multivariate Cox regression analysis. The combined colon cancer database includes 2,137 tumor samples from 17 independent cohorts. The most significant genes associated with relapse-free survival with a false discovery rate below 1% in colon cancer carcinoma were RBPMS (hazard rate [HR] = 2.52), TIMP1 (HR = 2.44), and COL4A2 (HR = 2.36). The three strongest genes associated with shorter survival in stage II colon cancer include CSF1R (HR = 2.86), FLNA (HR = 2.88), and TPBG (HR = 2.65). In summary, a new integrated database for colon cancer is presented. A colon cancer analysis subsystem was integrated into our Kaplan-Meier plotter that can be used to mine the entire database (https://www.kmplot.com). The portal has the potential to be employed for the identification and prioritization of promising biomarkers and therapeutic target candidates in multiple solid tumors including, among others, breast, lung, ovarian, gastric, pancreatic, and colon cancers.
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Colorectal cancer, recognized as a quintessential age-related disease, underscores the intricate interplay between aging mechanisms and disease pathogenesis. Cellular senescence, a DNA damage-induced cellular stress response, is characterized by cell cycle arrest, the expression of an inflammatory senescence-associated secretory phenotype, and alterations in extracellular matrix metabolism. It is widely recognized as a fundamental and evolutionarily conserved mechanism of aging. Guided by geroscience principles, which assert that the pathogenesis of age-related diseases involves cellular mechanisms of aging, this study delves into the role of senescence-related genes in colon cancer progression. Leveraging a gene set reflective of senescence-associated pathways, we employed uni- and multivariate Cox proportional hazards survival analysis combined with the determination of the false discovery rate to analyze correlations between gene expression and survival. The integrated database of 1130 colon cancer specimens with available relapse-free survival time and relapse event data from ten independent cohorts provided a robust platform for survival analyses. We identified senescence-related genes associated with differential expression levels linked to shorter survival. Our findings unveil a prognostic signature utilizing cellular senescence-related genes (hazard ratio: 2.73, 95% CI 2.12-3.52, p = 6.4E - 16), offering valuable insights into survival prediction in colon cancer. Multivariate analysis underscored the independence of the senescence-related signature from available epidemiological and pathological variables. This study highlights the potential of senescence-related genes as prognostic biomarkers. Overall, our results underscore the pivotal role of cellular senescence, a fundamental mechanism of aging, in colon cancer progression.
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Senescência Celular , Neoplasias Colorretais , Humanos , Senescência Celular/genética , Neoplasias Colorretais/genética , Neoplasias Colorretais/mortalidade , Neoplasias Colorretais/patologia , Prognóstico , Masculino , Feminino , Idoso , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Biomarcadores Tumorais/genéticaRESUMO
The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem. Here we mine large scale MM proteogenomic data integrating it with MM cell line dependency screen, and drug sensitivity data to identify druggable targets and forecast treatment efficacy and resistance. Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC and AKT1, across five distinct MM subtypes. These proteins serve as potential drug targets applicable to one or multiple MM subtypes. By analyzing transcriptomic data from 48 publicly accessible melanoma cell lines sourced from Achilles and CRISPR dependency screens, we forecasted 162 potentially targetable genes. We also identified genetic resistance in 260 genes across at least one melanoma subtype. In addition, we employed publicly available compound sensitivity data (Cancer Therapeutics Response Portal, CTRPv2) on the cell lines to assess the correlation of compound effectiveness within each subtype. We have identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype. Remarkably, employing this unbiased approach, we have uncovered compounds targeting ferroptosis, that demonstrate a striking 30x fold difference in sensitivity among different subtypes. This implies that the proteogenomic classification of melanoma has the potential to predict sensitivity to ferroptosis compounds. Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy. Highlights: (1) Proteogenomic subtype classification can define the landscape of genetic dependencies in melanoma (2) Nine proteins from molecular subtypes were identified as potential drug targets for specified MM patients (3) 20 compounds identified that show potential effectiveness in at least one melanoma subtype (4) Proteogenomics can predict specific ferroptosis inducers, HDAC, and RTK Inhibitor sensitivity in melanoma subtypes.
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Mediator kinases CDK19 and CDK8, pleiotropic regulators of transcriptional reprogramming, are differentially regulated by androgen signaling, but both kinases are upregulated in castration-resistant prostate cancer (CRPC). Genetic or pharmacological inhibition of CDK8 and CDK19 reverses the castration-resistant phenotype and restores the sensitivity of CRPC xenografts to androgen deprivation in vivo. Prolonged CDK8/19 inhibitor treatment combined with castration not only suppressed the growth of CRPC xenografts but also induced tumor regression and cures. Transcriptomic analysis revealed that Mediator kinase inhibition amplified and modulated the effects of castration on gene expression, disrupting CRPC adaptation to androgen deprivation. Mediator kinase inactivation in tumor cells also affected stromal gene expression, indicating that Mediator kinase activity in CRPC molded the tumor microenvironment. The combination of castration and Mediator kinase inhibition downregulated the MYC pathway, and Mediator kinase inhibition suppressed a MYC-driven CRPC tumor model even without castration. CDK8/19 inhibitors showed efficacy in patient-derived xenograft models of CRPC, and a gene signature of Mediator kinase activity correlated with tumor progression and overall survival in clinical samples of metastatic CRPC. These results indicate that Mediator kinases mediated androgen-independent in vivo growth of CRPC, supporting the development of CDK8/19 inhibitors for the treatment of this presently incurable disease.
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Quinase 8 Dependente de Ciclina , Quinases Ciclina-Dependentes , Neoplasias de Próstata Resistentes à Castração , Inibidores de Proteínas Quinases , Ensaios Antitumorais Modelo de Xenoenxerto , Masculino , Humanos , Animais , Neoplasias de Próstata Resistentes à Castração/patologia , Neoplasias de Próstata Resistentes à Castração/tratamento farmacológico , Neoplasias de Próstata Resistentes à Castração/genética , Neoplasias de Próstata Resistentes à Castração/metabolismo , Neoplasias de Próstata Resistentes à Castração/enzimologia , Camundongos , Quinases Ciclina-Dependentes/antagonistas & inibidores , Quinases Ciclina-Dependentes/genética , Quinases Ciclina-Dependentes/metabolismo , Quinase 8 Dependente de Ciclina/antagonistas & inibidores , Quinase 8 Dependente de Ciclina/genética , Quinase 8 Dependente de Ciclina/metabolismo , Linhagem Celular Tumoral , Inibidores de Proteínas Quinases/farmacologia , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Microambiente Tumoral/efeitos dos fármacosRESUMO
Patients with estrogen receptor-positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs. SIGNIFICANCE: This study advances the understanding of therapy-induced dormancy with potential clinical implications for breast cancer. Estrogen receptor-positive breast cancer cells adapt to endocrine treatment by entering a dormant state characterized by strong heterochromatinization with no recurrent genetic changes. Targeting the epigenetic rewiring impairs the adaptation of cancer cells to ETs. See related commentary by Llinas-Bertran et al., p. 704. This article is featured in Selected Articles from This Issue, p. 695.
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Neoplasias da Mama , Epigênese Genética , Humanos , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Neoplasias da Mama/tratamento farmacológico , Feminino , Recidiva Local de Neoplasia/genética , Regulação Neoplásica da Expressão GênicaRESUMO
The identification of surfaceome proteins is a main goal in cancer research to design antibody-based therapeutic strategies. T cell engagers based on KLK2, a kallikrein specifically expressed in prostate cancer (PRAD), are currently in early clinical development. Using genomic information from different sources, we evaluated the immune microenvironment and genomic profile of prostate tumors with high expression of KLK2. KLK2 was specifically expressed in PRAD but it was not significant associated with Gleason score. Additionally, KLK2 expression did not associate with the presence of any immune cell population and T cell activating markers. A mild correlation between the high expression of KLK2 and the deletion of TMPRSS2 was identified. KLK2 expression associated with high levels of surface proteins linked with a detrimental response to immune checkpoint inhibitors (ICIs) including CHRNA2, FAM174B, OR51E2, TSPAN1, PTPRN2, and the non-surface protein TRPM4. However, no association of these genes with an outcome in PRAD was observed. Finally, the expression of these genes in PRAD did not associate with an outcome in PRAD and any immune populations. We describe the immunologic microenvironment on PRAD tumors with a high expression of KLK2, including a gene signature linked with an inert immune microenvironment, that predicts the response to ICIs in other tumor types. Strategies targeting KLK2 with T cell engagers or antibody-drug conjugates will define whether T cell mobilization or antigen release and stimulation of immune cell death are sufficient effects to induce clinical activity.
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Calicreínas , Neoplasias da Próstata , Receptores Odorantes , Humanos , Masculino , Genômica , Calicreínas/genética , Calicreínas/imunologia , Calicreínas/metabolismo , Proteínas de Neoplasias , Neoplasias da Próstata/genética , Neoplasias da Próstata/imunologia , Neoplasias da Próstata/metabolismo , Tetraspaninas , Microambiente Tumoral/genéticaRESUMO
Approximately 30% of early-stage breast cancer (BC) patients experience recurrence after systemic chemotherapy; thus, understanding therapy resistance is crucial in developing more successful treatments. Here, we investigated the mechanisms underlying resistance to combined anthracycline-taxane treatment by comparing gene expression patterns with subsequent therapeutic responses. We established a cohort of 634 anthracycline-taxane-treated patients with pathological complete response (PCR) and a separate cohort of 187 patients with relapse-free survival (RFS) data, each having transcriptome-level expression data of 10,017 unique genes. Patients were categorized as responders and non-responders based on their PCR and RFS status, and the expression for each gene was compared between the two groups using a Mann-Whitney U-test. Statistical significance was set at p < 0.05, with fold change (FC) > 1.44. Altogether, 224 overexpressed genes were identified in the tumor samples derived from the patients without PCR; among these, the gene sets associated with xenobiotic metabolism (e.g., CYP3A4, CYP2A6) exhibited significant enrichment. The genes ORAI3 and BCAM differentiated non-responders from responders with the highest AUC values (AUC > 0.75, p < 0.0001). We identified 51 upregulated genes in the tumor samples derived from the patients with relapse within 60 months, participating primarily in inflammation and innate immune responses (e.g., LYN, LY96, ANXA1). Furthermore, the amino acid transporter SLC7A5, distinguishing non-responders from responders, had significantly higher expression in tumors and metastases than in normal tissues (Kruskal-Wallis p = 8.2 × 10-20). The identified biomarkers underscore the significance of tumor metabolism and microenvironment in treatment resistance and can serve as a foundation for preclinical validation studies.