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PI3Kγ inhibition drives M1 macrophage differentiation and synergizes with PD-L1 blockade to improve survival in poorly immunogenic head and neck squamous cell carcinoma.
[BACKGROUND] Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally with high mortality rates, highlighting the urgent need for novel therapeutic strategies. We investigated the efficacy of combining phosphoi…
FULLTEXT: multiple-instance learning -
Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.
Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has improved survival across multiple cancer types, but the variability in patient response h…
FULLTEXT: multiple-instance learning -
Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.
Increasing evidence suggests that Graves' disease (GD) may increase the risk of thyroid cancer (THCA), but diagnostic biomarkers associated with it remain underexplored. To address this issue, we analyzed the Gene Expression Omnibus (GEO) a…
FULLTEXT: multiple-instance learning -
Interaction between ZMIZ2 and AR promotes prostate cancer proliferation in vitro and in vivo.
[BACKGROUND] ZMIZ2, an androgen receptor (AR) transcriptional co-regulator, promotes prostate cancer (PCa) cell proliferation by interacting with AR to upregulate genes associated with cell proliferation; however, its specific cooperative m…
FULLTEXT: multiple-instance learning -
Exploring the key functions of T cells and the regulation of the immune microenvironment in prostate cancer using single-cell RNA sequencing and bulk RNA sequencing.
The incidence of prostate cancer continues to increase, making it the second most common malignant tumor among men worldwide. Immunotherapy has emerged as a key therapeutic strategy for treating tumors. Numerous studies have established tha…
FULLTEXT: multiple-instance learning -
Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis.
[BACKGROUND] Prostate cancer (PCa) is a leading cause of male cancer-related death globally. While the gut microbiota is linked to PCa, its genetic association remains unclear. [METHODS] We screened genetic instruments related to the gut m…
FULLTEXT: multiple-instance learning -
Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.
[OBJECTIVE] To construct and interpret a machine learning model for predicting overall survival in nonsurgical prostate cancer with bone metastases (PCBM). [METHODS] Data from 3,378 SEER database patients were utilized to develop machine l…
FULLTEXT: multiple-instance learning -
A dual diacylglycerol kinase (DGK) alpha/zeta inhibitor augments the activity of human tumor infiltrating lymphocytes in and models.
Endogenous or adoptively transferred tumor-infiltrating lymphocytes (TILs) often lose their functional capacity due to the activation of intrinsic inhibitory pathways, which then limits their ability to control tumor growth. In this study, …
FULLTEXT: multiple-instance learning -
Passive nuclear transport deviates from Fickian behavior in prostate and breast cell types.
Nuclear trafficking is essential for cellular function and biomedical applications such as nucleus-targeted drug delivery; however, how passive nuclear transport varies across cell types and phenotypic states remains poorly understood. Here…
FULLTEXT: multiple-instance learning -
Steroid receptor coactivator 3-deficient regulatory T cells eradicate multiple solid tumors in syngeneic mouse models.
Steroid receptor coactivator 3 (SRC-3) is highly expressed in regulatory T cells (Tregs) and is important for their immunosuppressive activity. Recently, we demonstrated that disrupting SRC-3 expression in Tregs eliminates triple-negative b…
FULLTEXT: multiple-instance learning -
Temporal trends in second primary malignancies among long-term survivors of multiple myeloma across treatment eras: a population-based analysis of the SEER database.
[OBJECTIVE] To evaluate temporal trends in second primary malignancy (SPM) risk among long-term multiple myeloma (MM) survivors across treatment eras. [METHODS] This retrospective cohort study utilized the SEER 17 registries database (1975…
FULLTEXT: multiple-instance learning -
A systematic assessment of the short- and long-term effects of commonly used breast cancer chemotherapeutics on the gut microbiome‒blood‒brain axis of female mice.
Chemotherapy affects over 300,000 U.S. breast cancer patients, which disrupts the gut microbiome and induces gut inflammation-an effect hypothesized to drive gastrointestinal side effects (e.g., diarrhea, vomiting) experienced by 50%-80% of…
FULLTEXT: multiple-instance learning -
Polymersome-based nanomedicine for combined cancer therapy.
Cancer is a complex disease characterized by uncontrolled cell growth and spread, often resulting in metastasis. The use of combination therapy, which involves the simultaneous application of two or more treatment methods, aims to enhance e…
FULLTEXT: multiple-instance learning -
IL-37/IL-1R8 axis: a novel major mechanism of control at the interface between tumor and immune cells.
Interleukin (IL)-37 is one of the "youngest" IL-1 family members and one of the few molecules exerting anti-inflammatory activity. Upon inflammasome activation, the cytokine precursor is converted into its mature form, which acts intracellu…
FULLTEXT: multiple-instance learning -
Clomiphene citrate in the management of anovulation: a review of mechanisms, outcomes, and clinical challenges.
[OBJECTIVE] To review the mechanism of action, epidemiology, clinical efficacy, factors influencing treatment outcomes, and limitations of clomiphene citrate (CC). [METHODS] A systematic literature search was conducted using electronic dat…
FULLTEXT: multiple-instance learning -
Microbiota as a modulator of drug response: targeting microbial-drug crosstalk in cancer therapy.
In recent years, accumulating evidence has established mechanistic connections between the microbiota and the efficacy of anticancer treatments, encompassing microbial communities residing in the gut, within tumors, and across other tissue …
FULLTEXT: multiple-instance learning -
Locus-specific transcriptional regulation of transposable elements by p53.
The tumor suppressor p53 protects genomic integrity in part by regulating transposable elements (TEs). Studies of p53-TE interactions rely on synthetic DNA and reporter assays, estimating expression only at the family or subfamily level and…
FULLTEXT: multiple-instance learning -
Dynamic changes in cellular mechanics and membrane microviscosity during migration of colorectal cancer cells.
The ability of tumor cells to migrate and invade adjacent tissue is a key property underlying the metastatic process. To ensure greater deformability and to facilitate movement, migratory cells undergo multiple changes in biophysical parame…
FULLTEXT: multiple-instance learning -
Prolonged progression-free survival with zanubrutinib in relapsed/refractory CLL: an indirect treatment comparison versus other BTK inhibitors using multilevel network meta-regression.
[BACKGROUND] Bruton tyrosine kinase inhibitors (BTKis) are therapeutic agents for relapsed/refractory chronic lymphocytic leukemia (R/R CLL). Previous indirect treatment comparisons are limited in simultaneously comparing multiple intervent…
FULLTEXT: multiple-instance learning -
Identification and functional exploration of hub genes related to energy metabolism in acute myeloid leukemia.
[OBJECTIVES] Acute myeloid leukemia (AML) is an aggressive hematological malignancy with poor prognosis. Abnormal energy metabolism is a well-recognized cancer hallmark, yet the role of energy metabolism-related genes (EMRGs) in AML remains…
FULLTEXT: multiple-instance learning