Ovarian cancer is a deadly gynecological malignancy that will affect about 21,000 women and result in almost 153,000 deaths in the United States in 2025. New clinical tools that facilitate early diagnosis and treatment of ovarian malignancies will significantly help reduce mortality and improve current long-term survival rates. We utilized a previously identified single-strand DNA aptamer RLA01 that binds and internalizes into target epithelial ovarian cancer cells to label PLGA-based nanoparticles and determine their ability to selectively target EOC cells and deliver payloads for cellular internalization. Nanoparticles labeled with RLA01 significantly enhanced cellular uptake 20-85% by receptor-mediated endocytosis into target EOC Caov-3 cells and inhibited cellular uptake in non-target HOSE 6-3 cells. Further, labeling of paclitaxel-loaded nanoparticles with RLA01 significantly decreased cell proliferation and induced apoptosis. A preliminary pilot study looking at the in vivo stability of aptamers demonstrated their ability to promote retention and honing of nanoparticles at tumors. These data demonstrate the effective combinatorial use of aptamer RLA01 and nanoparticle technologies for the direct targeting of tumor cell populations both in vitro and in vivo.

Colorectal cancer (CRC) is not only the third most common cancer worldwide, with 1.1 million new cases per year; it is also the second leading cause of cancer death. However, mortality has decreased since 2012 due to early detection programs and better therapeutic approaches. While many patients are diagnosed at an early stage, there is up to 50% relapse after optimal initial treatment. Therefore, it is crucial to explore the mechanism underlying the development of recurrences and metastasis. It is known that tumors release dormant cells that escape chemotherapy and nest in a target organ without proliferating. Under certain circumstances that are not yet entirely clear, they can be activated and metastasize. Therefore, the objective of this work is to explore the detailed mechanisms of dormancy, including early detection of recurrence and therapeutic approaches for the treatment of CRC. The specific objectives are to determine biomarkers that may be useful in identifying dormant cells to detect minimal residual disease (MRD) after surgery and predicting disease progression, as well as evaluating biomarkers that are susceptible to therapeutic intervention.

MicroRNA-211 (miR-211) is a versatile regulatory molecule that plays critical roles in cellular homeostasis and disease progression through the post-transcriptional regulation of gene expression. This review comprehensively examines miR-211's multifaceted functions across various biological systems, highlighting its context-dependent activity as both a tumor suppressor and oncogene. In physiological contexts, miR-211 regulates cell cycle progression, metabolism, and differentiation through the modulation of key signaling pathways, including TGF-β/SMAD and PI3K/AKT. miR-211 participates in retinal development, bone physiology, and protection against renal ischemia-reperfusion injury. In pathological conditions, miR-211 expression is altered in various diseases, particularly cancer, where it may be a useful diagnostic and prognostic biomarker. Its stability in serum and differential expression in various cancer types make it a promising candidate for non-invasive diagnostics. The review also explores miR-211's therapeutic potential, discussing both challenges and opportunities in developing miRNA-based treatments. Understanding miR-211's complex regulatory interactions and context-dependent functions is crucial for advancing its clinical applications for diagnosis, prognosis, and targeted therapy in multiple diseases.

Early diagnosis of lung cancer is crucial for improving patient prognosis. In this study, we developed a diagnostic model for lung cancer based on serum proteomic data from the GSE168198 dataset using four machine learning algorithms (nnet, glmnet, svm, and XGBoost). The model's performance was validated on datasets that included normal controls, disease controls, and lung cancer data containing both. Furthermore, the model's diagnostic capability was further validated on an independent external dataset. Our analysis identified SLC16A4 as a key protein in the model, which was significantly downregulated in lung cancer serum samples compared to normal controls. The expression of SLC16A4 was closely associated with clinical pathological features such as gender, tumor stage, lymph node metastasis, and smoking history. Functional assays revealed that overexpression of SLC16A4 significantly inhibited lung cancer cell proliferation and induced cellular senescence, suggesting its potential role in lung cancer development. Additionally, correlation analyses showed that SLC16A4 expression was linked to immune cell infiltration and the expression of immune checkpoint genes, indicating its potential involvement in immune escape mechanisms. Based on multi-omics data from the TCGA database, we further discovered that the low expression of SLC16A4 in lung cancer may be regulated by DNA copy number variations and DNA methylation. In conclusion, this study not only established an efficient diagnostic model for lung cancer but also identified SLC16A4 as a promising biomarker with potential applications in early diagnosis and immunotherapy.

Tumor drug resistance, a major cause of treatment failure, involves complex multi-gene networks, remodeling of signaling pathways, and interactions with the tumor microenvironment. Yin Yang 1 (YY1) is a critical oncogene overexpressed in many tumors and mediates multiple tumor-related processes, such as cell proliferation, metabolic reprogramming, immune evasion, and drug resistance. Notably, YY1 drives resistance through multiple mechanisms, such as upregulation of drug efflux, maintenance of cancer stemness, enhancement of DNA repair capacity, modulation of the tumor microenvironment, and epithelial-mesenchymal transition, thereby positioning it as a pivotal regulator of drug resistance. This review examines the pivotal role of YY1 in resistance, elucidating its molecular mechanisms and clinical relevance. We demonstrate that YY1 inhibition could effectively reverse drug resistance and restore therapeutic sensitivity across various treatment modalities. Importantly, we highlight the promising potential of YY1-targeted strategies, particularly combined with anti-tumor agents, to overcome resistance barriers. Furthermore, we discuss critical translational considerations for advancing these combinatorial approaches into clinical practice.

Breast cancer, the most prevalent malignancy among women worldwide, exhibits significant heterogeneity, particularly in the tumor microenvironment (TME), which poses challenges for treatment. Spatial transcriptomics (ST) has emerged as a transformative technology, enabling gene expression analysis while preserving tissue spatial architecture. This provides unprecedented insights into tumor heterogeneity, cellular interactions, and disease mechanisms, offering a powerful tool for advancing breast cancer research and therapy. This review aims to synthesize the applications of ST in breast cancer research, focusing on its role in decoding tumor heterogeneity, characterizing the TME, elucidating progression and metastasis dynamics, and predicting therapeutic responses. We also explore how ST can bridge molecular profiling with clinical translation to enhance precision therapy. The key scientific concepts of review included the following: We summarize the technological advancements in ST, including imaging-based and sequencing-based methods, and their applications in breast cancer. Key findings highlight how ST resolves spatial heterogeneity across molecular subtypes and histological variants. ST reveals the dynamic interplay between tumor cells, immune cells, and stromal components, uncovering mechanisms of immune evasion, metabolic reprogramming, and therapeutic resistance. Additionally, ST identifies spatial prognostic markers and predicts responses to chemotherapy, targeted therapy, and immunotherapy. We propose that ST serves as a hub for integrating multi-omics data, offering a roadmap for precision oncology and personalized treatment strategies in breast cancer.

Magnetic resonance imaging (MRI) has a pivotal role in both pretreatment staging and post-treatment evaluation of rectal cancer. This study presents an innovative deep learning model, CAAFE-ResNet18*, based on the residual neural network ResNet18*. The model features an ingeniously designed feature extraction and complementation module (i.e., CAAFE), which leverages a multiscale dilated convolution parallel architecture combined with a channel attention mechanism (CAM) to achieve multilevel information fusion, spatial feature enhancement and channel feature optimisation. This enables in-depth exploration and augmentation of multilevel downsampled features, significantly improving feature representation capability and overall performance. Testing on rectal cancer MRI data demonstrates that the CAAFE-ResNet18* model significantly outperforms convolutional neural network (CNN) backbone networks and recent state-of-the-art (SOTA) models. This result indicates that the CAAFE model, by complementing and extracting MR images of patients with locally advanced rectal cancer (LARC) features at different scales from ResNet18*, may help to identify patients who will show complete response (CR) at the end of treatment and those who will not respond to therapy (NR) at an early stage of the treatment.

The treatment of Cutaneous Squamous Cell Carcinoma (CSCC) has undergone significant changes with the introduction of Immune Checkpoint Inhibitors (ICIs). While promising results have been observed, their efficacy remains limited to a subset of patients. Soluble immune checkpoint molecules, Interferon-gamma (IFN-γ), and cell-free DNA (cfDNA) could serve as potential biomarkers, particularly in ICI-based therapies.

Radiotherapy (RT) is a standard curative treatment for prostate cancer (PCa) and there is growing evidence of the high efficacy of moderate and ultra-hypofractionated RT. Reducing treatment duration to one week or less is a major advance, but very few studies have explored single-fraction therapy. This study evaluates the feasibility, safety, and efficacy of single-fraction stereotactic body RT (SBRT) while delivering the entire procedure in one day, with a potentially high benefit in terms of patient comfort and therapy cost and logistics.

Achieving optimal surgical margins is critical in breast-conserving surgery (BCS) to reduce local recurrence (LR) and the need for re-excision. This meta-analysis evaluated the impact of intraoperative margin optimization strategies on key surgical and oncologic outcomes in patients who underwent BCS.

Melanoma, a highly aggressive and immunogenic skin cancer, often develops resistance to immunotherapy due to the immunosuppressive tumor microenvironment (TME). Although PD-1/PD-L1 inhibitors have significantly improved treatment outcomes, 30%-40% of patients exhibit no response or develop resistance. Mechanisms such as T-cell exhaustion within the TME limit therapeutic efficacy, necessitating the exploration of novel strategies to enhance immune responses.

Current consensus guidelines lack robust evidence to advocate the optimal treatment approach for locoregional upper esophageal squamous cell carcinoma (L-UESCC). The purpose of this study was to conduct an in-depth investigation of the treatment patterns, outcomes, and prognostic factors among patients with L-UESCC.

The advent of targeted therapy and immunotherapy has revolutionised the management of hepatocellular carcinoma (HCC) patients with all stages, dramatically improving their survival outcomes. Currently, radical resection is still the preferred first-line treatment for early-stage HCC, nevertheless, the surgical outcomes remain unsatisfactory due to high recurrence rate of 70% within 5 years after surgery. Moreover, up to two thirds of diagnosed HCC patients are in the advanced stages of the disease, exhibiting intrahepatic or extrahepatic metastases and vascular invasion. In recent years, the combination of surgical and other local treatments with targeted therapy and immunotherapy has dramatically improved the overall survival for HCC patients and also increased the complexity of HCC management, demanding a dynamic adaptation of the available staging-based strategies and flexible therapeutic allocation. In this review, we mainly elaborate the fundamental principles and recent advancements in the surgical management of locally advanced HCC, such as neoadjuvant, adjuvant and conversion therapy, as well as the regulatory effects of local treatments on targeted therapy and immunotherapy. Finally, the value of splenectomy for unresectable HCC patients with hypersplenism is also discussed.

Acral melanoma (AM) is the predominant subtype of melanoma in Asians. Early detection and prevention can significantly improve patient outcomes; however, there is a lack of effective early biomarkers for predicting AM metastasis. Here, we employed single-cell and spatial transcriptomics analyses to investigate early microsatellite lesions of AM and identify biomarkers of invasiveness in these lesions. Our results characterize a highly immunosuppressive microenvironment and metabolic process shifts in early AM microsatellite lesions that promote the metastatic potential. The transcription factor SOX6 is overexpressed in microsatellite lesions and marks a population of highly invasive melanoma cells. The pro-invasive role of overexpressed SOX6 was validated in vivo and in vitro, including its ability to enhance tumor invasion by upregulating cellular glycolysis, disrupt fatty acid transport, and increase intracellular phosphatidylcholine content. This study suggests that SOX6-overexpressing melanoma cells are the main driver subpopulation promoting early invasion of AM and establishes SOX6 and fatty acid transport processes as biomarkers and potential therapeutic targets for early melanoma metastasis.

Small-cell lung cancer (SCLC) is an aggressive malignancy with a poor prognosis. Despite the initial chemosensitivity, survival for extensive-disease (ED) SCLC remains limited. Immune checkpoint inhibitors (ICIs) in combination with chemotherapy have recently been redefined as the standard of care. We evaluated the efficacy of ICI combination therapy in clinical trials translated into real-world clinical practice for patients with ED-SCLC.

Pathologically, intrahepatic cholangiocarcinoma (ICC) is classified into small-duct (SD) type and large-duct (LD) type, each with distinct clinicopathological characteristics. The contrast-enhanced ultrasound (CEUS) features of the two ICC types remain insufficiently explored.

Brain metastases (BrMs) frequently manifest in patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC), and the optimal treatment approach for these individuals remains controversial. This study aimed to evaluate the cost-effectiveness of adding pemetrexed-platinum chemotherapy to first-line gefitinib in EGFR-mutant NSCLC patients with BrMs, considering the perspective of the Chinese healthcare system.

Nutritional risk assessment indices impact disease prognosis, yet their prognostic roles in preoperative digestive system tumor (DST) patients remain unclear.

Accurate delineation of Gross Tumor Volume (GTV) in lung cancer is critical for effective radiotherapy and surgical planning. However, segmentation of GTV in high-resolution CT images remains challenging, particularly when tumors are small or have indistinct boundaries.

Pathological diagnosis is important for the treatment of deep suprahyoid head and neck lesions, and tissue sampling needs to balance minimal invasiveness and accuracy. The purpose of this study was to evaluate diagnostic accuracy and factors associated with diagnostic failure of core needle biopsy (CNB) with CT-guided in deep suprahyoid head and neck lesions.