Clinical Management Of Cancer Research Articles

MicroRNA-145-5p inhibits the tumorigenesis of breast cancer through SENP2-regulated ubiquitination of ERK2

Breast carcinoma exhibits the highest incidence among various cancers and is the foremost cause of mortality in women. Increasing evidence shows that SUMOylation of proteins plays a critical role in the progression of breast cancer; however, the role of SENP2 and its molecular mechanism in breast cancer remain underexplored. Here, we discerned that SENP2 promoted the tumorigenesis of breast cancer both in vitro and in vivo. Furthermore, we identified that ERK2 was SUMOylated and that SENP2 played a role by deconjugating ERK2 SUMOylation in breast cancer. SUMOylation of ERK2 promoted its ubiquitin-proteasomal degradation, thus inhibiting the epithelial-to-mesenchymal transition in breast cancer cells. Furthermore, microRNA-145-5p (miR-145-5p) has emerged as a scarce commodity in breast cancer and binds to the 3’-untranslated region of SENP2 mRNA to govern the regulatory dynamics of SENP2 expression. Finally, miR-145-5p inhibits SENP2 transcription, enhances ERK2 SUMOylation, and ultimately suppresses the progression of breast cancer. These revelations suggest evolving ideas for the miR-145-5p-SENP2 axis in therapeutic intervention, thus heralding transformative prospects for the clinical management of breast cancer.

Persistent luminescent nanoprobes with dual effect radiosensitization for precise radiotherapy

Radiotherapy (RT) is a common modality in the clinical management of breast cancer. However, the radiation damage to healthy tissues caused by the high-dose radiation and the limited therapeutic efficacy with DNA damage repair pose significant challenges in RT. In this work, an intelligent responsive nanoplatform with dual effect radiosensitization (mZGSSM-AMD) has been developed to improve the efficacy of RT. The doping of Lu promotes the generation of reactive oxygen species (ROS) under X-ray irradiation, thereby facilitating DNA breakage. To hinder the repair of damaged DNA, NO is loaded into mZGSSM-AMD, enhancing damage of tumor during radiotherapy. Furthermore, persistent luminescence (PersL) recovers with the degradation of MnO2 in tumor microenvironment (TME), which guides precision radiosensitization of tumors. Experimental results indicate that growth of tumors is significantly suppressed by effective radiosensitization of mZGSSM-AMD. The mZGSSM-AMD with dual effect radiosensitization exhibits exceptional antitumor effectiveness, providing promising application prospects for the imaging-guided precise radiosensitization therapy.

PTPN20 promotes metastasis through activating NF-κB signaling in triple-negative breast cancer

BackgroundCancer metastasis remains a major challenge in the clinical management of triple-negative breast cancer (TNBC). The NF-κB signaling pathway has been implicated as a crucial factor in the development of metastases, but the underlying molecular mechanisms remain largely unclear.MethodsPTPN20 expression was evaluated using data from the Sweden Cancerome Analysis Network-Breast and The Cancer Genome Atlas database, as well as by western blotting and immunohistochemistry in 88 TNBC patients. The ability of PTPN20 to activate NF-κB was assessed by luciferase reporter assays. The effects of PTPN20 overexpression and knockdown via short hairpin RNA were examined in TNBC cell lines by wound healing and transwell matrix penetration assays. Additionally, we analyzed the growth and metastasis abilitiy of 4T1 xenograft tumors in nude mice.ResultsPTPN20 levels were elevated in TNBC cell lines and patient samples compared to controls, and higher protein levels correlated with metastasis-free survival. Overexpression of PTPN20 enhanced migration and invasion in vitro, and promoted lung metastasis in vivo. Our finding revealed that PTPN20 activates NF-κB signaling by dephosphorylating p65 at Ser468, preventing its binding to COMMD1, thereby protecting p65 from degradation. Downregulation of PTPN20 effectively inhibit, while p65 S468A mutant restored the migratory and invasive abilities of TNBC cells.ConclusionsCollectively, our results demonstrate that PTPN20 plays a critical role in TNBC metastasis through the activation of NF-κB signaling. We propose that PTPN20 may serve as a novel prognostic marker and potential therapeutic target for the treatment of TNBC.

Self-assembly nanomedicine initiating cancer-immunity cycle with cascade reactions for boosted immunotherapy

Immune checkpoint blockade (ICB) therapy has been extensively integrated into cancer clinical management. However, its overall response rate is limited due to the stagnating cancer-immunity cycle (CIC) caused by the immunosuppressive tumor microenvironment (TME). Here, a multi-pronged nanomedicine, defined as LCCS, was constructed by the self-assembly of lactate oxidase, catalase, chlorin e6, and sorafenib. Through cascade reactions, LCCS effectively reprogrammed the TME and re-initiated the CIC by depleting lactate, alleviating hypoxia, inducing immunogenic cell death, and normalizing tumor vessels. Immunological analyses indicated that treatment with LCCS decreased the infiltration of immunosuppressive cells while increasing the recruitment of immune effector cells in tumors. Leveraging the effective operation of the CIC, LCCS improved the efficacy of ICB therapy to inhibit breast cancer, and effectively induced the elimination of colorectal cancer and long-term immune memory. Therefore, multifunctional nanomedicines targeting CIC hold great potential for applications in cancer immunotherapy.

Investigating High-risk Factors, Precise Diagnosis, and Treatment of Castration- Resistant Prostate Cancer (CRPC).

The treatment of metastatic castration-resistant prostate cancer (mCRPC) in the actual world currently presents difficulties. In light of this, it is crucial to investigate high-risk factors for the progression of advanced prostate cancer and to identify methods for delaying the onset of CRPC. This study aimed to explore the high-risk factors that impact the progression of prostate cancer and emphasize the significance of precise diagnosis and treatment based on etiological classification in the clinical management of castration-resistant prostate cancer. A retrospective analysis was conducted on 277 newly diagnosed cases of PCa treated with endocrine therapy. A follow-up was done on prostate-specific antigen (PSA) levels and testosterone. Additionally, a prospective analysis was performed on the clinical data of 60 patients with CRPC. Following the principle of "4W1H", 30 patients were included in the precision treatment group for a second biopsy and related tests, while another 30 patients were included in the conventional treatment group. The therapeutic effect and prognosis of the two groups were observed. Distant metastasis (HR = 1.879, 95% CI: 1.311 ~ 2.694, P = 0.001), PSA nadir > 0.2 ng/mL (HR = 1.843, 95% CI: 1.338 ~ 2.540, P = 0.001), testosterone nadir > 20 ng/dL (HR = 1.403, 95% CI: 1.035 ~ 1.904, P = 0.029), and time to testosterone nadir > 6 months (HR = 1.919, 95% CI: 1.364 ~ 2.701, P = 0.001) were risk factors for the progression to CRPC. Patients in the CRPC group were treated with precision therapy and conventional therapy based on their molecular subtyping. The precision treatment group showed a significantly prolonged median PSA progression-free survival compared to the conventional treatment group (16.0 months vs. 13.0 months, P=0.025). The median radiographic progression-free survival was also significantly extended in the precision treatment group compared to the conventional treatment group (21.0 months vs. 16.0 months, P=0.042). Patients with prostate cancer diagnosed with distant metastasis at initial presentation require early intervention. Close monitoring of PSA and serum testosterone changes is necessary during the process of endocrine therapy. After entering the CRPC stage, the etiological classification precision treatment can improve the therapeutic effect and improve the prognosis of patients.

Therapeutic Immunomodulation of Tumor-Lymphatic Crosstalk via Intratumoral Immunotherapy.

Intra- and peritumoral lymphatics and tumor-draining lymph nodes play major roles in mediating the adaptive immune response to cancer immunotherapy. Despite this, current paradigms of clinical cancer management seldom seek to therapeutically modulate tumor-lymphatic immune crosstalk. This review explores recent developments that set the stage for how this regulatory axis can be therapeutically manipulated, with a particular emphasis on tumor-localized immunomodulation. Building on this idea, the nature of tumor-lymphatic immune crosstalk and relevant immunotherapeutic targets and pathways are reviewed, with a focus on their translational potential. Engineered drug delivery systems that enhance intratumoral immunotherapy by improving drug delivery to both the tumor and lymph nodes are also highlighted.

Accelerated hazard prediction based on age time-scale for women diagnosed with breast cancer using a deep learning method

Breast cancer is the most common cancer in women. Previous studies have investigated estimating and predicting the proportional hazard rates and survival in breast cancer. This study deals with predicting accelerated hazards (AH) rate based on age categories in breast cancer patients using deep learning methods. The AH has a time-dependent structure whose rate changes according to time and variable effects. We have collected data related to 1225 female patients with breast cancer at the Mandarin University of Medical Sciences. The patients' demographic and clinical characteristics including family history, age, history of tobacco use, hysterectomy, first menstruation age, gravida, number of breastfeeding, disease grade, marital status, and survival status have been recorded. Initially, we dealt with predicting three age groups of patients: ≤ 40, 41–60, and ≥ 61 years. Then, the prediction of accelerated risk value based on age categories for each breast cancer patient through deep learning and the importance of variables using LightGBM is discussed. Improving clinical management and treatment of breast cancer requires advanced methods such as time-dependent AH calculation. When the behavioral effect is assumed as a time scale change between hazard functions, the AH model is more appropriate for randomized clinical trials. The study results demonstrate the proper performance of the proposed model for predicting AH by age categories based on breast cancer patients' demographic and clinical characteristics.

A pH and glutathione-responsive carbon monoxide-driven nano-herb delivery system for enhanced immunotherapy in colorectal cancer

Dihydroartemisinin (DHA), a compound extracted from the herbal medicine Artemisia annua, has shown promise as a clinical treatment strategy for colorectal cancer. However, its clinical use is hindered by its low water solubility and bioavailability. A pH/glutathione (GSH) dual-responsive nano-herb delivery system (PMDC NPs) has been developed for the targeted delivery of DHA, accompanied by abundant carbon monoxide (CO) release. Due to the passive enhanced permeability and retention (EPR) effect and active targeting mediated by pHCT74 peptide binding to overexpressed α-enolase on colorectal cancer cells, the pHCT74/MOF-5@DHA&CORM-401 nanoparticles (PMDC NPs) exhibited specific targeting capacity against colorectal cancer cells. Once reaching the tumor site, the pH/GSH dual-responsive behavior of metal-organic framework-5 (MOF-5) enabled the rapid release of cargo, including DHA and CORM-401, in the acidic tumor microenvironment. Subsequently, DHA stimulated CORM-401 to release CO, which facilitated ROS-induced ferroptosis and apoptosis, leading to immunogenic cell death (ICD) and a sustained antitumor response through the release of tumor-associated antigens (TAAs) and damage-associated molecular patterns (DAMPs). Overall, PMDC NPs enhanced the bioavailability of DHA and exhibited outstanding therapeutic effectiveness both in vitro and in vivo, indicating their potential as a promising and feasible alternative for synergistic treatment with immunotherapy and gas therapy in the clinical management of colorectal cancer.

A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6

BackgroundBreast cancer is a significant public health issue worldwide, being the most prevalent cancer among women and a leading cause of death related to this disease. The molecular processes that propel breast cancer progression are not fully elucidated, highlighting the intricate nature of the underlying biology and its crucial impact on global health. The objective of this research was to perform bioinformatics analyses on breast cancer-related datasets to gain a comprehensive understanding of the molecular mechanisms at play and to identify key genes associated with the disease.MethodsThe toolkit analyses involve techniques such as differential gene expression analysis, Gene Set Enrichment Analysis (GSEA), Weighted Co-Expression Network Analysis (WGCNA), and Machine Learning algorithms. Furthermore, in vitro cell experiments have demonstrated the impact of HSPB6 on cell migration, proliferation, and apoptosis.ResultsThe study identified multiple genes that displayed differential expression in breast cancer, notably FHL1 and HSPB6. A machine learning model was developed in this study and specifically trained for breast cancer diagnosis using these genes, achieving high precision. Furthermore, analysis of immune cell infiltration revealed an enrichment of Tregs and M2 macrophages in the treated group, showcasing its significant impact on the tumor’s immunological context. A temporal analysis of breast cancer cells using single-cell RNA sequencing provided insights into cellular developmental trajectories and highlighted changes in expression patterns across key genes during disease progression. The upregulation of HSPB6 in MCF7 cells significantly inhibited both cell migration and proliferation abilities, suggesting that promoting HSPB6 expression could induce ferroptosis in breast cancer cells.ConclusionOur findings have identified compelling molecular targets and distinctive diagnostic markers for the clinical management of breast cancer. This data will serve as crucial guidance for further research in the field.

SMAC mimetic BV6 acts in synergy with mTOR inhibitor to increase cisplatin sensitivity in ovarian cancer.

The objective of this study is to observe the antitumor efficacy of the second mitochondria-derived activator of caspases (SMAC) mimetic bivalent smac mimetic (BV6) in combination with target of rapamycin (mTOR) inhibitor on DDP (cisplatin) sensitivity. Ovarian cancer cells were exposed to cisplatin, BV6, DDP + BV6, and DDP + BV6 + mTOR inhibitor Rapamycin. Using proteomics and bioinformatics, protein expression profiles in ovarian cancer were determined. Bagg Albino color nude mice were treated with DDP or BV6 alone or in combination, or BV6 + DDP + Rapamycin. The effects of different treatments on ovarian cancer cells and tumor growth were evaluated in vivo and in vitro. Proteomics and bioinformatics analysis revealed significant changes of protein kinase (AKT)/mTOR pathway. Consistently, western blot data indicated that AKT/mTOR axis was gradually activated in BV6-treated ovarian cancer cells and attenuated the cytotoxic effect of BV6. Functional assays showed that DDP or BV6 treatment alone significantly enhanced the sensitivity and inhibited the migration of ovarian cancer cells, but without any synergistic effects. In addition, combination with BV6 and mTOR inhibitor Rapamycin significantly decreased cell viability and inhibited migration of ovarian cancer cells exposed to DDP. Consistently, the xenograft model showed that co-treatment with Rapamycin with BV6 had significantly suppressed tumor growth and metastasis. Our study demonstrated that SMAC analogue BV6 exhibits a strong anticancer effect on ovarian cancer in vitro and in vivo. Combination with Rapamycin overcomes the activation of mTOR pathway by BV6 and increases the chemosensitivity to DDP. These data suggest a potential application of triple combination with DDP + BV6 + Rapamycin in clinical management of ovarian cancer.

Analyzing the Mutational Landscape of Prostate Cancer Susceptibility Genes through Next-Generation Sequencing (NGS) Analysis

Prostate cancer, a significant public health concern, exhibits a complex genetic landscape influenced by a variety of susceptibility genes. This study deciphers the intricate genetic makeup of prostate cancer by examining mutations in 14 prostate cancer susceptibility genes. The Next-Generation Sequencing (NGS) approach was employed on a cohort of 45 prostate cancer patients to detect mutations. The gnomAD database was used to analyze mutational frequencies in the Asian population suffering from prostate cancer. The cBioPortal database was employed to check the presence of observed mutations in The Cancer Genome Atlas (TCGA) dataset. In addition, this study employed RT-qPCR and Immunohistochemistry (IHC) techniques were utilized to check the functional consequences of the observed pathogenic mutations. Finally, Metascape and DrugBank resources were used for gene enrichment and drug prediction analyses. Results of the NGS analysis revealed a total of 29 mutations (pathogenic and benign) within the examined prostate cancer cohort, distributed across four key genes (BRCA1/2, TP53, and PMS2) out of the total analyzed 14 genes. Pathogenic mutations in BRCA1/2 and TP53 genes are of particular interest due to their fundamental roles in DNA repair, cell cycle regulation, and tumor suppression. Functional consequence analyses (RT-qPCR and IHC) demonstrated the down-regulation of BRCA1/2 and TP53 genes in prostate cancer samples with pathogenic mutations, reinforcing the disruption of their tumor suppressor roles. Lastly, drug prediction analysis uncovered promising therapeutic options by identifying drugs capable of enhancing the mRNA expression of these genes. This opens new avenues for tailored treatment strategies aimed at restoring normal cellular functions of the BRCA1/2 and TP53 genes. In conclusion, this study provides a comprehensive view of genetic mutations in prostate cancer susceptibility genes, ranging from benign to pathogenic. It emphasizes the genetic complexity of prostate cancer and offers insights into potential mechanisms driving this malignancy. These findings lay the groundwork for further research, personalized treatment approaches, and enhanced clinical management of prostate cancer.

Management of de novo Metastatic Hormone-Sensitive Prostate Cancer (mHSPC) and the role of Radiation Therapy: A Consensus by the Italian Association of Radiotherapy and Clinical Oncology (AIRO)

Prostate cancer treatments paradigms are in continuous evolution, especially in metastatic setting. In this context, the Genito-Urinary (GU) Group of Italian Association of Radiotherapy and Clinical Oncology (AIRO) aimed to create a Consensus on radiotherapy indication in de novo metastatic hormone sensitive prostate cancer both on primary tumour and metastatic sites. A panel of experts, involved in clinical management of prostate cancer, through the estimate-talk-estimate (ETE) method, developed a list of items and correspondent statements on the identified topic. Seven conclusive items were identified with 12 statements about the chosen topic, radiotherapy in metastatic hormone sensitive prostate cancer on primary tumour and metastatic sites. This consensus might help clinicians in prostate cancer managing in daily clinical practice.

S610 Evaluating The Presentation and Clinical Management of Rare Secondary Esophageal Cancers From Breast Metastasis Origin: A Comprehensive Review of Case Reports

S610 Evaluating The Presentation and Clinical Management of Rare Secondary Esophageal Cancers From Breast Metastasis Origin: A Comprehensive Review of Case Reports

A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET-Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study.

Salvage radiation therapy (sRT) is often the sole curative option in patients with biochemical recurrence after radical prostatectomy. After sRT, we developed and validated a nomogram to predict freedom from biochemical failure. This study aims to evaluate prostate-specific membrane antigen-positron emission tomography (PSMA-PET)-based sRT efficacy for postprostatectomy prostate-specific antigen (PSA) persistence or recurrence. Objectives include developing a random survival forest (RSF) model for predicting biochemical failure, comparing it with a Cox model, and assessing predictive accuracy over time. Multinational cohort data will validate the model's performance, aiming to improve clinical management of recurrent prostate cancer. This multicenter retrospective study collected data from 13 medical facilities across 5 countries: Germany, Cyprus, Australia, Italy, and Switzerland. A total of 1029 patients who underwent sRT following PSMA-PET-based assessment for PSA persistence or recurrence were included. Patients were treated between July 2013 and June 2020, with clinical decisions guided by PSMA-PET results and contemporary standards. The primary end point was freedom from biochemical failure, defined as 2 consecutive PSA rises >0.2 ng/mL after treatment. Data were divided into training (708 patients), testing (271 patients), and external validation (50 patients) sets for machine learning algorithm development and validation. RSF models were used, with 1000 trees per model, optimizing predictive performance using the Harrell concordance index and Brier score. Statistical analysis used R Statistical Software (R Foundation for Statistical Computing), and ethical approval was obtained from participating institutions. Baseline characteristics of 1029 patients undergoing sRT PSMA-PET-based assessment were analyzed. The median age at sRT was 70 (IQR 64-74) years. PSMA-PET scans revealed local recurrences in 43.9% (430/979) and nodal recurrences in 27.2% (266/979) of patients. Treatment included dose-escalated sRT to pelvic lymphatics in 35.6% (349/979) of cases. The external outlier validation set showed distinct features, including higher rates of positive lymph nodes (47/50, 94% vs 266/979, 27.2% in the learning cohort) and lower delivered sRT doses (<66 Gy in 57/979, 5.8% vs 46/50, 92% of patients; P<.001). The RSF model, validated internally and externally, demonstrated robust predictive performance (Harrell C-index range: 0.54-0.91) across training and validation datasets, outperforming a previously published nomogram. The developed RSF model demonstrates enhanced predictive accuracy, potentially improving patient outcomes and assisting clinicians in making treatment decisions.

Abstract PR-02: Uncovering molecular differences in pancreatic ductal adenocarcinoma tissues from Black and White patients in the US

Abstract Background: Pancreatic cancer (PC) is among the leading causes of cancer-related deaths in the United States, with a 5-year survival rate of approximately 13%. Previous studies reported higher PC incidence and mortality rates among Black or African American (BAA) patients in comparison to White patients. Disadvantaged socioeconomic status (SES) and environmental exposure to chemicals are factors contributing to racial disparities in pancreatic cancer. Whether and how biological pathways play roles in disparities in pancreatic cancer is unclear. The understanding of molecular features associated racial backgrounds in pancreatic cancer will have significant impacts on both scientific inquiry on cancer biology and clinical management of pancreatic malignancy. In this study, we examined oncogene alterations and PD-L1 expression in pancreatic cancer patients of diverse racial backgrounds. Methods: We conducted our study by analyzing clinical test results of patients through a collaboration with Tempus Labs. In total, 4,249 pancreatic cancer patients’ (White: 3797 and BAA: 452) information were included in this study. DNA target panel sequencing was performed to identify genomic mutations. Genomic microsatellite instability (MSI) and tumor mutational burdens (TMB) were assessed. We also evaluated PD-L1 expression by immunohistochemistry. Results: DNA sequencing analysis revealed differential gene mutation profiles between White and BAA patients. We observed higher rates of KRAS (79.2% vs. 74.2%, q=0.14), TP53 (69.9% vs. 61.9%, q=0.014), KMT2C (6.9% vs. 2.3%, q=0.001), RNF43 (6% vs. 3.7%, q=0.14), and KMT2D (4.4% vs. 2.8%, q=0.3) mutations among BAA patients compared to White patients whereas fewer GNAS (0.2% vs 1.6%, q=0.14) mutation occur in the BAA group. Importantly, the KRAS mutant allele KRASG12R was significantly enriched in BAA compared to White patients (14.4% vs. 10.1%). Next, we compared the TMB levels and found that BAA patients showed higher average TMB levels when compared to White patients. Further, we determined the expression of PD-L1 between the two racial groups and observed BAA patients had more frequent PD-L1 overexpression than White patients (13.2% vs. 8.6%, p&amp;lt;0.05). Interestingly, the race associated difference in PD-L1 expression was even more remarkable in female groups (14.1% vs. 8%, p&amp;lt;0.05). Conclusion: We observed differences in mutation profiles of oncogenes between BAA and White patients, suggesting that such molecular-level changes may contribute to the higher incidence among BAA patients. Additionally, higher frequencies of PD-L1 upregulation in BAA patients implicate racial backgrounds influence tumor microenvironment regulation in pancreatic cancer patients. It is imperative to improve racial diversity in translational and clinical studies. Citation Format: Saurabh Mandal, Emily A Teslow, Minxuan Huang, Swathi Sridhar, Howard Crawford, Melissa C Stoppler, Albert Levin, Ling Huang. Uncovering molecular differences in pancreatic ductal adenocarcinoma tissues from Black and White patients in the US [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr PR-02.

Additional reporting of diffuse and homogeneous ROS-1 SP384 immunoreactivity enhances prediction of ROS1 fusion-positive non-small cell lung cancer.

ROS-1 immunohistochemistry (IHC) is a common method for screening ROS1 fusion in the clinical management of non-small cell lung cancer. The interpretation criteria for ROS-1 SP384 IHC, however, remain unestablished. Sixty-five non-small cell lung cancer cases underwent AmoyDx ROS1 fusion real-time polymerase chain reaction (PCR) study and ROS-1 SP384 IHC tests, which were retrieved for analysis. ROS-1 IHC tests were interpreted based on the established classifiers as well as the presence of diffuse homogeneous immunoreactivity. The diagnostic accuracies of these ROS-1 IHC interpretation methods were evaluated by comparing them with the ROS1 real-time PCR results. Previous ROS-1 IHC classifiers demonstrated high sensitivity for positive ROS1 real-time PCR results (100%), but they showed low specificities (25%-50%) and overall accuracies (58%-72%). In contrast, the diffuse homogeneous ROS-1 immunoreactivity predicted positive ROS1 real-time PCR results with much higher specificity (94%) and overall accuracy (95%), albeit with a slightly lower sensitivity (97%). Some cases that showed discrepancy between diffuse homogeneous ROS-1 immunoreactivity and real-time PCR results involved rare ROS1::LDLR fusion and suboptimal IHC staining. A 3-tier reporting system for ROS-1 SP384 IHC testing combining previous interpretation criteria and diffuse and homogeneous immunoreactivity may better predict ROS1 fusion status without decreasing specificity.

Identification of lysine lactylation (kla)-related lncRNA signatures using XGBoost to predict prognosis and immune microenvironment in breast cancer patients

Breast cancer (BC) stands as a predominant global malignancy, significantly contributing to female mortality. Recently uncovered, histone lysine lactylation (kla) has assumed a crucial role in cancer progression. However, the correlation with lncRNAs remains ambiguous. Scrutinizing lncRNAs associated with Kla not only improves clinical breast cancer management but also establishes a groundwork for antitumor drug development. We procured breast tissue samples, encompassing both normal and cancerous specimens, from The Cancer Genome Atlas (TCGA) database. Utilizing Cox regression and XGBoost methods, we developed a prognostic model using identified kla-related lncRNAs. The model's predictive efficacy underwent validation across training, testing, and the overall cohort. Functional analysis concerning kla-related lncRNAs ensued. We identified and screened 8 kla-related lncRNAs to formulate the risk model. Pathway analysis disclosed the connection between immune-related pathways and the risk model of kla-related lncRNAs. Significantly, the risk scores exhibited a correlation with both immune cell infiltration and immune function, indicating a clear association. Noteworthy is the observation that patients with elevated risk scores demonstrated an increased tumor mutation burden (TMB) and decreased tumor immune dysfunction and exclusion (TIDE) scores, suggesting heightened responses to immune checkpoint blockade. Our study uncovers a potential link between Kla-related lncRNAs and BC, providing innovative therapeutic guidelines for BC management.

Spatial landscapes of cancers: insights and opportunities.

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Tubal Cancer Clinical Management: Two Exceptional Scenarios and a Review of the Literature.

This article provides a literature review on tubal carcinoma to offer an updated insight into its preventative strategies, diagnosis, treatment and oncological surveillance. In addition to the search string utilized, the authors' focus extended to key scientific studies, consensus statements, guidelines and relevant case reports essential for the proper clinical management of the disease, providing a methodologically well-structured literature review combined with practical expertise in the oncological field. This article also includes two special clinical cases that emphasize the importance of understanding the physiopathology and the current state of the art in the anatomopathological advancements in tubal/ovarian/peritoneal carcinoma, often assimilated into a single clinical entity and to which many of the concepts extracted from the literature can apply.

Targeting colorectal cancer with Herba Patriniae and Coix seed: Network pharmacology, molecular docking, and in vitro validation

BACKGROUND Herba Patriniae and Coix seed (HC) constitute a widely utilized drug combination in the clinical management of colorectal cancer (CRC) that is known for its diuretic, anti-inflammatory, and swelling-reducing properties. Although its efficacy has been demonstrated in a clinical setting, the active compounds and their mechanisms of action in CRC treatment remain to be fully elucidated. AIM To identify the active, CRC-targeting components of HC and to elucidate the mechanisms of action involved. METHODS Active HC components were identified and screened using databases. Targets for each component were predicted. CRC-related targets were obtained from human gene databases. Interaction targets between HC and CRC were identified. A “drug-ingredient-target” network was created to identify the core components and targets involved. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to elucidate the key pathways involved. Molecular docking between core targets and key components was executed. In vitro experiments validated core monomers. RESULTS Nineteen active components of HC were identified, with acacetin as the primary active compound. The predictive analysis identified 454 targets of the active compounds in HC. Intersection mapping with 2685 CRC-related targets yielded 171 intervention targets, including 30 core targets. GO and KEGG analyses indicated that HC may influence the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. Molecular docking showed that acacetin exhibited an optimal interaction with AKT1 , identifying PI3K , AKT , and P53 as key genes likely targeted by HC during CRC treatment. Acacetin inhibited HT-29 cell proliferation and migration, as well as promoted apoptosis, in vitro . Western blotting analysis revealed increased p53 and cleaved caspase-3 expression and decreased levels of p-PI3K , p-Akt , and survivin, which likely contributed to CRC apoptosis. CONCLUSION Acacetin, the principal active compound in the HC pair, inhibited the proliferation and migration of HT-29 cells and promoted apoptosis through the PI3K/Akt/p53 signaling pathway.