Integration of mRNA and protein expression data for the identification of potential biomarkers associated with pancreatic ductal adenocarcinoma

LncRNA FAM30A Suppresses Proliferation and Metastasis of Colorectal Carcinoma by Blocking the JAK-STAT Signalling

Colorectal carcinoma (CRC) poses a serious risk to global human health. Long non-coding RNAs (LncRNAs) play an important role in the pathogenesis of CRC. There is a scarcity of data about a newly identified lncRNA, FAM30A. Our major objective is to investigate the role of FAM30A in the process of CRC. Gene expression data and correlated clinical information were retrieved and downloaded from public databases to identify differentially expressed genes linked to CRC. The expression of FAM30A was identified in clinical samples and CRC cell lines using via Quantitative Real-time Polymerase Chain Reaction (qPCR) assay also. The survival significance of FAM30A was determined via R package "survival." Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to identify FAM30A-related signalling pathway. The levels of proteins expression were determined by western blot assay. The effect of FAM30A on CRC cell biological behaviours was evaluated by cell function experiments. FAM30A was identified down-regulated in CRC based on the data from public database. FAM30A had lower expression in CRC clinical samples and cell lines. Low FAM30A expression was positively related to a poor prognosis in CRC patients. After FAM30A was overexpressed, the proliferation, invasion, and migration abilities of CRC cells were decreased, and the rate of CRC cell apoptosis increased. Furthermore, overexpression of FAM30A could block JAK-STAT signalling. FAM30A suppresses proliferative, invasive, and migratory abilities of CRC through blocking JAK-STAT signalling. Thus, it can be a novel biomarker of CRC prognosis.

Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target

Introduction

Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor microenvironment, particularly in BC. However, the glycosylation-related genes associated with TNBC have not yet been defined. Additionally, their characteristics and relationship with prognosis have not been deeply investigated.

Methods

Transcriptomic analyses were used to identify a glycosylation-related signature (GRS) associated with TNBC prognosis. A machine learning-based prediction model was constructed and validated across multiple independent datasets. The model's predictive capability was extended to evaluate the prognosis of TNBC individuals, tumor immune microenvironment and immunotherapy response. LMAN1L (Lectin, Mannose Binding 1 Like) was identified as a novel prognostic marker in TNBC, and its biological effects were validated through experimental assays.

Results

The GRS showed significant prognostic relevance for TNBC patients. The risk model effectively predicted molecular features, including immune cell infiltration and potential responses to immunotherapy. Experimental validation confirmed LMAN1L as a novel glycosylation-related prognostic gene, with low expression significantly inhibiting TNBC cell proliferation and migration.

Discussion

Our GRS risk model demonstrates robust predictive capability for TNBC prognosis and immunotherapy response. This model offers a promising strategy for personalized treatment and improved clinical outcomes in TNBC.

Overexpression of ZFP69B promotes hepatocellular carcinoma growth by upregulating the expression of TLX1 and TRAPPC9

BACKGROUND

T-cell leukemia homeobox protein 1 (TLX1) has been revealed as a hub transcription factor in leukemia, while its function in hepatocellular carcinoma (HCC) has not been well described. Here, we investigated the regulation and function of TLX1 in HCC.

METHODS

TLX1 and its possible upstream and downstream molecules in HCC were identified using bioinformatics tools, which were then verified by RT-qPCR assay. CCK-8, wound healing, and Transwell invasion assays were performed to detect the effects of TLX1 knockdown on HCC cells. The interactions between TLX1 and trafficking protein particle complex subunit 9 (TRAPPC9) or Zinc finger protein 69 homolog B (ZFP69B) were further probed by ChIP and luciferase reporter assays. Rescue experiments were finally conducted in vitro and in vivo.

RESULTS

TLX1 was highly expressed in HCC cells, and the knockdown of TLX1 led to reduced malignant biological behavior of HCC cells. TLX1 bound to the promoter region of TRAPPC9, thereby promoting TRAPPC9 expression. Overexpression of TRAPPC9 attenuated the effect of TLX1 reduction on suppressing malignant behavior of HCC cells. ZFP69B was also highly expressed in HCC cells and bound to the promoter region of TLX1 to induce TLX1 expression. Knockdown of ZFP69B inhibited the viability and mobility of HCC cells in vitro and tumor growth in vivo, and overexpression of TLX1 rescued this inhibition.

CONCLUSION

These findings suggest that ZFP69B promotes the proliferation of HCC cells by directly upregulating the expression of TLX1 and the ensuing TRAPPC9.

Stem cell-based targeted therapy in pancreatic cancer: Current approaches and future prospects

Despite recent improvements in oncology, diagnosis, and therapy, pancreatic cancer remains extremely difficult to cure due to its aggressive growth pattern with early invasion and distant metastases, chemoresistance, and a lack of effective screening modalities for early detection. Here, novel therapeutic approaches for treating pancreatic cancer are urgently needed. Recently, stem cells have drawn a lot of interest as a possible treatment for pancreatic cancer due to their ability to locate tumors. Though research over the last few decades has revealed some very exciting and promising new treatment approaches, the clinical success of these stem-cell based anti-cancer medicines has been quite limited. The most effective stem cell-mediated therapeutic options will only be available with a deeper understanding of the intricate molecular biology underlying pancreatic cancer and the subsequent identification of cancer stem cells as a novel target that promotes the growth of the cancer and resistance to chemotherapy. This review will highlight the stem cell based anti-cancer therapy targeting pancreatic cancer stem cells and different molecular signaling pathways. A particular focus will be on the therapeutic potential of naïve Stem cells, anti-cancer drug loaded stem cells, genetically engineered stem cells and exosomal miRNA released by stem cells in pancreatic cancer treatment. Similarly, the role of nanotechnology in stem cell based anticancer therapy will be further discussed to better implementation of these cell-based cancer therapy.

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.