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BACKGROUND: Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker-drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter- or intra-tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians. REVIEW: In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations. CONCLUSION: In recent years, exploration of subtypes through cell lines, animal models, patient-derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype-specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.
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Biomarcadores de Tumor , Neoplasias Colorrectales , Medicina de Precisión , Humanos , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/terapia , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/inmunología , Medicina de Precisión/métodos , Biomarcadores de Tumor/genética , AnimalesRESUMEN
Study of alternating DNA GC sequences by different time-resolved spectroscopies has provided fundamental information on the interaction between UV light and DNA, a process of great biological importance. Multiple decay paths have been identified, but their interplay is still poorly understood. Here, we characterize the photophysics of GC-DNA by integrating different computational approaches, to study molecular models including up to 6 bases described at a full quantum mechanical level. Quantum dynamical simulations, exploiting a nonadiabatic linear vibronic coupling (LVC) model, coupled with molecular dynamics sampling of the initial structures of a (GC)5 DNA duplex, provide new insights into the photophysics in the sub-picosecond time-regime. They indicate a substantial population transfer, within 50 fs, from the spectroscopic states towards G â C charge transfer states involving two stacked bases (CTintra), thus explaining the ultrafast disappearance of fluorescence. This picture is consistent with that provided by quantum mechanical geometry optimizations, using time dependent-density functional theory and a polarizable continuum model, which we use to parametrize the LVC model and to map the main excited state deactivation pathways. For the first time, the infrared and excited state absorption signatures of the various states along these pathways are comprehensively mapped. The computational models suggest that the main deactivation pathways, which, according to experiment, lead to ground state recovery on the 10-50 ps time scale, involve CTintra followed by interstrand proton transfer from the neutral G to C-. Our calculations indicate that CTintra is populated to a larger extent and more rapidly in GC than in CG steps and suggest the likely involvement of monomer-like and interstrand charge transfer decay routes for isolated and less stacked CG steps. These findings underscore the importance of the DNA sequence and thermal fluctuations for the dynamics. They will also aid the interpretation of experimental results on other sequences.
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Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.
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Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.
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Carcinoma Hepatocelular , Progresión de la Enfermedad , Epigénesis Genética , Transición Epitelial-Mesenquimal , Regulación Neoplásica de la Expresión Génica , Neoplasias Hepáticas , Metaloproteinasa 12 de la Matriz , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Carcinoma Hepatocelular/metabolismo , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Humanos , Transición Epitelial-Mesenquimal/genética , Pronóstico , Metaloproteinasa 12 de la Matriz/genética , Metaloproteinasa 12 de la Matriz/metabolismo , MicroARNs/genética , MicroARNs/metabolismo , Proliferación Celular/genética , Línea Celular Tumoral , Células Madre Neoplásicas/patología , Células Madre Neoplásicas/metabolismo , Metilación de ADNRESUMEN
BACKGROUND: Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC. METHODS: This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017-2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018-2021) and another from center 2 (n = 43, 2020-2021), were utilized to assess the signature's association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data. RESULTS: Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression. CONCLUSION: This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC's MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications.
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Radiómica , Neoplasias Gástricas , Humanos , Estudios de Cohortes , Neoplasias Gástricas/diagnóstico por imagen , Neoplasias Gástricas/genética , Neoplasias Gástricas/terapia , Estudios Retrospectivos , Inestabilidad de Microsatélites , Inmunoterapia , Tomografía Computarizada por Rayos X , InmunoglobulinasRESUMEN
AIMS: In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully sufficient to promptly recognize patients with early-stage hypertrophic cardiomyopathy (HCM) without symptomatic and instrumental features. Considering the sudden death of HCM, developing a novel diagnostic model to clarify the patients with early-stage HCM and the immunological characteristics can avoid misdiagnosis and attenuate disease progression. METHODS AND RESULTS: Three hundred eighty-five samples from four independent cohorts were systematically retrieved. The weighted gene co-expression network analysis, differential expression analysis (|log2(foldchange)| > 0.5 and adjusted P < 0.05), and protein-protein interaction network were sequentially performed to identify HCM-related hub genes. With a machine learning algorithm, the least absolute shrinkage and selection operator regression algorithm, a stable diagnostic model was developed. The immune-cell infiltration and biological functions of HCM were also explored to characterize its underlying pathogenic mechanisms and the immune signature. Two key modules were screened based on weighted gene co-expression network analysis. Pathogenic mechanisms relevant to extracellular matrix and immune pathways have been discovered. Twenty-seven co-regulated genes were recognized as HCM-related hub genes. Based on the least absolute shrinkage and selection operator algorithm, a stable HCM diagnostic model was constructed, which was further validated in the remaining three cohorts (n = 385). Considering the tight association between HCM and immune-related functions, we assessed the infiltrating abundance of various immune cells and stromal cells based on the xCell algorithm, and certain immune cells were significantly different between high-risk and low-risk groups. CONCLUSIONS: Our study revealed a number of hub genes and novel pathways to provide potential targets for the treatment of HCM. A stable model was developed, providing an efficient tool for the diagnosis of HCM.
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Cardiomiopatía Hipertrófica , Aprendizaje Automático , Humanos , Cardiomiopatía Hipertrófica/genética , Cardiomiopatía Hipertrófica/diagnóstico , Perfilación de la Expresión Génica/métodos , Manejo de la Enfermedad , MasculinoRESUMEN
Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.
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Neoplasias , Estructuras Linfoides Terciarias , Humanos , Inteligencia Artificial , Pronóstico , Neoplasias/terapia , Linfocitos B/patología , Fenotipo , Microambiente Tumoral , Estructuras Linfoides Terciarias/genética , Estructuras Linfoides Terciarias/patologíaRESUMEN
BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of singlecell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.
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Adenocarcinoma , Neoplasias Pulmonares , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , Análisis de Secuencia de ARN , Reparación del ADN , Pulmón , Neoplasias Pulmonares/genética , Microambiente Tumoral/genéticaRESUMEN
PURPOSE: Long noncoding RNAs (lncRNAs) were recently implicated in modifying pyroptosis. Nonetheless, pyroptosis-related lncRNAs and their possible clinical relevance persist largely uninvestigated in lung adenocarcinoma (LUAD). MATERIALS AND METHODS: A sum of 921 samples were collected from three independent data sets. We obtained pyroptosis-related genes from both the Molecular Signatures Database and relevant literature sources and used four machine learning techniques, comprising stepwise Cox, ridge regression, least absolute shrinkage and selection operator, and random forest. Multiple bioinformatics approaches were used to further investigate the underlying mechanisms. RESULTS: In total, 39 differentially expressed pyroptosis genes were identified by comparing normal and tumor samples. Correlation analysis revealed 933 pyroptosis-related lncRNAs. Furthermore, univariate Cox regression determined 11 lncRNAs that exhibited stable associations with prognosis in the three cohorts, which were used to construct the pyroptosis-derived lncRNA signature. After analyzing the optimal results from four machine learning algorithms, we ultimately selected random forest to develop the pyroptosis-derived lncRNA signature. This signature was proven to be an independent prognostic factor and exhibited robust performance in three cohorts. CONCLUSION: We provided novel insight and established a pyroptosis-derived lncRNA signature for patients with LUAD, exhibiting strong predictive capabilities in both the training and validation sets.
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Adenocarcinoma , ARN Largo no Codificante , Humanos , Piroptosis , ARN Largo no Codificante/genética , Pronóstico , Adenocarcinoma/diagnóstico , Adenocarcinoma/genética , PulmónRESUMEN
The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC.
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Amina Oxidasa (conteniendo Cobre) , Muerte Celular , Neoplasias Colorrectales , Humanos , Autofagia/genética , Biomarcadores , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/metabolismo , Pronóstico , Amina Oxidasa (conteniendo Cobre)/genética , Amina Oxidasa (conteniendo Cobre)/metabolismo , Moléculas de Adhesión Celular/genética , Moléculas de Adhesión Celular/metabolismoRESUMEN
BACKGROUND: In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine. CONCLUSION: This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.
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Oncología Médica , Neoplasias , Medicina de Precisión , Humanos , Medicina de Precisión/métodos , Neoplasias/genética , Neoplasias/clasificación , Neoplasias/metabolismo , Oncología Médica/métodos , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Genómica/métodos , Proteómica/métodosRESUMEN
Epigenetic modifications impart important functionality to nucleic acids during gene expression but may increase the risk of photoinduced gene mutations. Thus, it is crucial to understand how these modifications affect the photostability of duplex DNA. In this work, the ultrafast formation (<20 ps) of a delocalized triplet charge transfer (CT) state spreading over two stacked neighboring nucleobases after direct UV excitation is demonstrated in a DNA duplex, d(G5fC)9â¢d(G5fC)9, made of alternating guanine (G) and 5-formylcytosine (5fC) nucleobases. The triplet yield is estimated to be 8 ± 3%, and the lifetime of the triplet CT state is 256 ± 22 ns, indicating that epigenetic modifications dramatically alter the excited state dynamics of duplex DNA and may enhance triplet state-induced photochemistry.
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ADN , Epigénesis Genética , ADN/química , ADN/efectos de la radiación , Rayos UltravioletaRESUMEN
The dynamics of excited electronic states in self-assembled structures formed between silver(I) ions and cytosine-containing DNA strands or monomeric cytosine derivatives were investigated by time-resolved infrared (TRIR) spectroscopy and quantum mechanical calculations. The steady-state and time-resolved spectra depend sensitively on the underlying structures, which change with pH and the nucleobase and silver ion concentrations. At pH â¼ 4 and low dC20 strand concentration, an intramolecularly folded i-motif is observed, in which protons, and not silver ions, mediate C-C base pairing. However, at the higher strand concentrations used in the TRIR measurements, dC20 strands associate pairwise to yield duplex structures containing C-Ag+-C base pairs with a high degree of propeller twisting. UV excitation of the silver ion-mediated duplex produces a long-lived excited state, which we assign to a triplet excimer state localized on a pair of stacked cytosines. The computational results indicate that the propeller-twisted motifs induced by metal-ion binding are responsible for the enhanced intersystem crossing that populates the triplet state and not a generic heavy atom effect. Although triplet excimer states have been discussed frequently as intermediates in the formation of cyclobutane pyrimidine dimers, we find neither computational nor experimental evidence for cytosine-cytosine photoproduct formation in the systems studied. These findings provide a rare demonstration of a long-lived triplet excited state that is formed in a significant yield in a DNA duplex, demonstrating that supramolecular structural changes induced by metal ion binding profoundly affect DNA photophysics.
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ADN , Plata , Emparejamiento Base , Plata/química , ADN/química , Citosina/química , ProtonesRESUMEN
In this work, a chemistry-informed generative model was proposed, leading to the chemistry-informed generative adversarial network (CI-GAN) approach. To easily build the input database for complex molecular systems, an image-input algorithm is also implemented, leading to the capability to directly recognize the molecular image. Extensive test calculations and analysis on typical examples, H + H2, OH + HO2, and H2O/TiO2(110), find that the present CI-GAN approach generates distributions of geometry and energy. Calculations on the above examples show that the present CI-GAN approach is able to generate 50%-80% meaningful results among all of the generated data with chemistry constraints. Thus, it has the potential capability to predict classical dynamics simulations as well as ab initio calculations avoiding expensive calculations. These results and the power of CI-GANs in generating ab initio energies and MD trajectories are deeply discussed.
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BACKGROUND: Multiple PDZ Domain Crumbs Cell Polarity Complex Component (MPDZ) is involved in a few human cancers. However, the features and potential mechanisms of MPDZ in progression of colorectal cancer (CRC) remains unknown. METHODS: The prognostic role of MPDZ in CRC was determined by Kaplan-Meier and univariate regression analysis. Enrichment analysis was performed to characterize crucial pathways of MPDZ. Immune infiltration and immunotherapeutic outcome were further evaluated. CCK8, EDU, transwell, and wound healing assay were used to assess the influence of MPDZ on pernicious performance of CRC cells. CD8+ T cells and CRC cells were co-cultured to explore the effect of MPDZ on the tumor microenvironment. qRT-PCR, western blot, immunoprecipitation (IP), and methylated RNA immunoprecipitation (me-RIP) were implemented in seeking for the potential mechanisms of MPDZ in CRC. RESULTS: CRC patients with elevated MPDZ expression suffered from significantly worse prognosis. Enrichment analysis revealed that MPDZ involved in pathways related to metastasis and cell cycle in CRC. In addition, MPDZ expression were related to several immunoinhibitors and had the ability to predict immunotherapy response. Finally, in vitro assays demonstrated that MPDZ knockdown inhibited migration, invasion and immune evasion of CRC cells. Mechanistically, MPDZ knockdown enhanced YAP1 phosphorylation by increased LATS1 expression. Moreover, m6A-MPDZ mRNA may be recognized and degraded by m6A recognition protein YTHDF2. CONCLUSIONS: MPDZ was critical for CRC development and could be a promising candidate for the treatment of CRC patients.
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Linfocitos T CD8-positivos , Neoplasias Colorrectales , Humanos , Linfocitos T CD8-positivos/metabolismo , Linfocitos T CD8-positivos/patología , Línea Celular Tumoral , Movimiento Celular/genética , Proliferación Celular/genética , Neoplasias Colorrectales/patología , Proteínas de la Membrana/metabolismo , Fosforilación , Factores de Transcripción/metabolismo , Microambiente Tumoral , Proteínas Señalizadoras YAP/metabolismoRESUMEN
OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: ⢠The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. ⢠Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. ⢠The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.
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Neoplasias de los Conductos Biliares , Tumor de Klatskin , Humanos , Masculino , Persona de Mediana Edad , Metástasis Linfática/patología , Tumor de Klatskin/diagnóstico por imagen , Tumor de Klatskin/cirugía , Radiómica , Estudios Retrospectivos , Tomografía Computarizada por Rayos X/métodos , Ganglios Linfáticos/patología , Neoplasias de los Conductos Biliares/diagnóstico por imagen , Neoplasias de los Conductos Biliares/cirugía , Neoplasias de los Conductos Biliares/patologíaRESUMEN
Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.