8 results about "Multiple cancer" patented technology

This invention discloses the application of P4HB as a target in the preparation of therapeutic drugs for metastatic pleural and peritoneal effusions in multiple cancer types. Through combined single-cell transcriptomics and proteomics analysis, this invention revealed that P4HB is significantly overexpressed in metastatic pleural and peritoneal effusion lesions. Multiplex immunofluorescence and immunohistochemistry were used to perform in situ tissue validation in clinical samples of pleural and peritoneal effusions from breast cancer, lung cancer, gastric cancer, colorectal cancer, and ovarian cancer, clarifying the differential expression characteristics of P4HB in metastatic tumor cells and its correlation with poor prognosis. In patient-derived organoid models, targeting and inhibiting P4HB activity with small molecule inhibitors significantly reduced organoid growth capacity and survival rate, and showed a synergistic sensitizing effect on chemotherapeutic drugs. This invention reveals the use of P4HB as a therapeutic target for metastatic pleural and peritoneal effusions in multiple cancer types, providing a new target and direction for drug development in precision medicine.

This invention provides a novel target nucleic acid molecule, P7, for the identification of multiple cancer types and its applications. A group of methylated target nucleic acid segments for the diagnosis of multiple pan-cancer diseases were screened and validated. These segments exhibited significant differences in methylation status within tumor samples, which can be used to identify individuals at high risk for cancer. When these target nucleic acid segments are used in combination for detection, they exhibit unexpected improvements in sensitivity and specificity. The tumor target nucleic acid segments of this invention can serve as novel molecules for auxiliary clinical diagnosis or prognosis of cancer.

This invention relates to a cancer signal identification method based on a cfDNA sequence language model and its application in cancer screening and MRD monitoring. The deep learning-based sequence language model analyzes whole-genome sequencing data of cfDNA to automatically extract and identify cancer-related signals, making it suitable for clinical scenarios such as early cancer screening and minimal residual disease (MRD) monitoring. This technology overcomes the limitations of targeting specific known mutations or manually labeled biomarkers, enabling end-to-end deep modeling of high-throughput whole-genome sequences of cfDNA. This significantly improves the sensitivity, specificity, and generalization ability of early cancer screening and MRD monitoring, providing an innovative solution for non-invasive screening of multiple cancer types and longitudinal disease monitoring.

This invention discloses a combination of protein biomarkers for screening multiple cancer types and its applications, belonging to the field of cancer diagnostic technology. The combination includes 164 candidate proteins such as IGLV4-60 and TPM3. This invention also provides an in vitro detection method, which involves extracting proteins from plasma or serum samples of subjects, enzymatically digesting them, and then using liquid chromatography-mass spectrometry to obtain the relative expression levels of the proteins; subsequently, the expression levels are input into a classification model constructed based on a machine learning algorithm. This invention employs a stratified screening strategy of first binary classification and then multi-class classification, which can not only distinguish between healthy individuals and cancer patients with high sensitivity and specificity, but also further accurately classify colorectal cancer, gastric cancer, liver cancer, lung cancer, ovarian cancer, and pancreatic cancer. This invention achieves non-invasive, high-throughput parallel screening and tissue tracing of multiple cancer types, possessing extremely high clinical application value.

The method may include receiving a positron emission tomography (PET) scan depicting multiple cancer cells. One or more lesions depicted in the PET scan may be identified. An origin cell classification model may be applied to determine the origin cells of each lesion depicted in the PET scan. A molecular subtype profile of multiple cancer cells depicted in the PET scan may be determined based on the origin cells of at least the individual lesions depicted in the PET scan. The molecular subtype profile may include the overall origin cells of the multiple cancer cells and / or the proportion of lesions having each possible origin cell. Related systems and computer program products are also provided.

The application belongs to the technical field of biological medicine, and particularly relates to a biomarker for early screening, diagnosis or monitoring of multiple cancers and application. The application realizes early high-precision screening and diagnosis of multiple cancers by screening and adopting a brand-new biomarker combination, namely, exosome surface phosphatidylserine (PS) and / or prolyl 4-hydroxylase beta subunit (P4HB), and the performance is significantly better than that of existing biomarkers. The technical scheme has the advantages of non-invasiveness, convenience, rapidness and the like, and simultaneously has high sensitivity and high specificity, and can realize accurate identification in the super-early or early stage of cancer, and is expected to develop into a new generation of non-invasive tumor diagnosis tool.

The present invention relates to methods for determining the concentration of cell-free DNA (cfDNA) from capillary electropherogram and calculating the proportion of short fragments from mono-nucleosomes. In some embodiments, the determination of cfDNA concentration and mono-nucleosome short fragment proportion, optionally in combination with a panel of screened protein biomarkers, can be used to achieve efficient and cost-effective early detection of multiple cancer types.

The present disclosure relates to methods for early detection of cancer. In some embodiments, a panel of selected markers is employed to achieve efficient and economically viable early detection of multiple cancer types.