Isobaric Tags for Relative and Absolute Quantitation in Proteomic Analysis of Potential Biomarkers in Invasive Cancer, Ductal Carcinoma In Situ, and Mammary Fibroadenoma

Clinical and Immunological Significance of ANKRD52 in Pan-Cancer

Ankyrin repeat domain 52 (ANKRD52) is a regulatory component of the protein phosphatase 6 (PP6) holoenzyme. Evidence has emerged to suggest involvement of ANKRD52 in tumor metastases and cancer cell escape from T cell-mediated elimination and immunotherapy but there has been no research across different cancer types. The current study explored the biological functions of ANKRD52 by combining data from many databases. The aim was to expose new diagnostic or treatment biomarkers for malignant tumors. The roles of ANKRD52 with respect to immunotherapy in 33 human cancer types were analyzed by combining data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), UCSC Xena, the Tumor Immune Estimation Resource (TIMER), TISIDB and Cellminer. Bioinformatics methods were used to analyze the association between ANKRD52 expression and prognosis, immunological indicators (immune cell infiltration, ESTIMATE scores and tumor microenvironment (TME) signatures), tumor mutational burden (TMB), microsatellite instability (MSI) and drug sensitivity. ANKRD52 expression was generally higher in 24 tumor tissues than in normal tissues and was associated with poor prognosis, especially in kidney chromophobe (KICH). Lower expression was observed in advanced cancer. ANKRD52 expression was strongly linked to major immunological indicators, such as immune cell infiltration, ESTIMATE scores, TME signatures, as well as expression of immune and tumor-related genes. Expression was also associated with indicators of immunotherapy efficacy and outcome, such as TMB in 7 cancer types and MSI in 12. In addition, ANKRD52 expression was linked to sensitivity to a number of anticancer drugs. ANKRD52 had a distinct immune function in breast invasive carcinoma (BRCA) that correlated negatively with most immune indicators. Expression was enriched in proliferation-, differentiation- and metabolism-related pathways and linked to other immune cells and TME signatures. A nomogram to predict 3- or 5-year overall survival (OS) of patients with BRCA was constructed. ANKRD52 may have utility as an oncological and immunological biomarker. New insights into oncogenesis are presented and the development of ANKRD52-targeting to increase the therapeutic efficacy of immunotherapy combined with chemotherapy explored.

Proteome profiling of ductal carcinoma in situ

BACKGROUND AND AIM

DCIS is the most common type of non-invasive breast cancer, accounting for about 15 to 30%. Proteome profile is used to detect biomarkers in the tissues of breast cancer patients by mass spectrometry. This study aimed to obtain the expression profile of DCIS proteome, and the expression profile of invasive biomarkers, and finally to introduce a dedicated biomarker panel to facilitate the prognosis and early detection for in situ breast cancer patients.

METHODS AND MATERIALS

In this study, 10 patients with breast cancer (DCIS) were studied. Benign (marginal) and cancerous tissue samples were obtained from patients for proteomics experiments. Initially, all tissue proteins were extracted using standard methods, and the proteins were separated using two-dimensional electrophoresis. Then, the expression amount of the extracted proteins was determined by ITRAQ. The data were analysed by R software, and gene ontology was utilised for describing the protein in detail.

RESULTS

30 spots on gel electrophoresis were found in the tumor tissue group (sample), and 15 spots in the margin group (control) with P < 0.05. Healthy and cancerous tissue gels showed that 5 spots had different expression. VWF, MMP9, ITGAM, MPO and PLG protein spots were identified using the site www.ebi.ac.uk/IPI. Finally, protein biomarkers for breast tumor tissue with margin were introduced with the names of P04406, P49915, P05323, P06733, and P02768.

DISCUSSION

There are 5 critical proteins in inducing cancer pathways especially complement and coagulation cascades. The hall markers of a healthy cell to be cancerous are proliferation, invasion, angiogenesis, and changes in the immune system. Hence, regulation of protein plays a key role in developing recurrence to breast cancer in margins.

iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

Quantitative proteomics characterization of cancer biomarkers and treatment

Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the poor correlation between genes and proteins. Quantitative proteomics, capable of quantifying the relatively different protein abundance in cancer patients, has been increasingly adopted in cancer research. Quantitative proteomics has great application potentials, including cancer diagnosis, personalized therapeutic drug selection, real-time therapeutic effects and toxicity evaluation, prognosis and drug resistance evaluation, and new therapeutic target discovery. In this review, the development, testing samples, and detection methods of quantitative proteomics are introduced. The biomarkers identified by quantitative proteomics for clinical diagnosis, prognosis, and drug resistance are reviewed. The challenges and prospects of quantitative proteomics for personalized medicine are also discussed.