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[BACKGROUND] Tumour microenvironment and cancer cells have constant interaction affecting cancer progression. Tumour-stroma ratio (TSR) in the tumour centre and desmoplastic reaction (DR) classification at the invasive margin are prognostic…

[OBJECTIVE] Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) has improved outcomes in colorectal cancer (CRC) patients with peritoneal metastases (PM), yet evidence regarding perioperative risk and long-term …

[OBJECTIVE] This study aimed to identify distinct frailty subtypes and their influencing factors, and to further explore the relationship between these frailty characteristics and the occurrence of symptomatic radiation pneumonitis (SRP) in…

[PURPOSE] Immunohistochemical (IHC) biomarkers such as estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 are essential for the classification and treatment of breast cancer. While radiomics-based models have demonstrated p…

[PURPOSE] Microscopy-based cancer cell classification traditionally relies on cell-based morphological features, while subcellular organelle organization remains underutilized. Existing machine learning methods often require manual preproce…

In the tumor microenvironment, tissue-resident macrophages (TRMs) promote malignant tumor progression, yet their tissue-specific heterogeneity and complex functions bring research challenges. This study analyzes the research status and tren…

[BACKGROUND] Twin molar pregnancy (TMP) represents one of the most complex and high-risk entities within the spectrum of gestational trophoblastic disease. Characterized by the coexistence of a potentially viable fetus and molar trophoblast…

[BACKGROUND] Determination of estrogen receptor (ER) and progesterone receptor (PR) status is critical for breast cancer subtyping and guiding endocrine therapy. Although immunohistochemistry (IHC) remains the diagnostic gold standard, it i…

Cancer represents a significant challenge to people's health and safety. Tumor biomarker detection plays a vital role in the precise diagnosis of cancer and finds widespread applications in cancer screening and pathological diagnosis. Exist…

Accurate subtyping of lung cancer is essential for improving patient prognosis and enabling personalized treatment. However, current clinical techniques are often time-consuming and heavily dependent on the operator's subjective judgment an…

Rapid assessment of chemotherapeutic response is essential for precision oncology but remains hindered by tumor heterogeneity and complex biological matrices. Here, we develop MetaRing, a programmable coffee-ring-derived plasmonic biosensor…

[OBJECTIVE] To develop and validate a robust, multimodal machine learning framework integrating radiomic and deep learning features from multiplex immunohistochemistry (mIHC) images for comprehensive outcome prediction in colorectal cancer …

Colorectal cancer (CRC) is a highly heterogeneous malignancy that is divided into four consensus molecular subtypes (CMSs), with CMS4 considered to be the worst type of CRC. The CMS classification has not been translated into clinical pract…

Accurate delineation of treatment targets and organs at risk (OARs) is essential to the success of radiotherapy (RT). Although artificial intelligence (AI)-based segmentation methods have successfully automated the delineation process, a re…

Tertiary lymphoid structures (TLSs) have emerged as key regulators of anti-tumor immunity and biomarkers for immunotherapy response in liver cancer, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and combi…

[BACKGROUND] Rapid detection of drug-resistant leukemia played a crucial role in formulating appropriate treatment plans for patients and improving their prognosis. In this research, an integrated optofluidic platform was developed to detec…

TL;DRThe results demonstrate that Raman spectroscopy, when integrated with multivariate analysis, enables the non-destructive tracking of leukemia cell responses to targeted therapy and may support the development of phenotyp…

TL;DRA novel multimodal deep learning framework that synergistically integrates 1D spectral and 2D spatiotemporal features that establishes a novel method for thyroid cancer diagnosis, achieving both exceptional diagnostic pe…

TL;DRThis hypothesis-generating study demonstrates that baseline CECT radiomics shows promise for predicting chemotherapy response in pediatric lymphoma.

TL;DRThe Multimodal Hybrid Mamba (MSHM) classification model for tumor pathological grade prediction and multimodal medical image analysis strikes a balance between high performance and efficiency, advancing both tumor pathol…