Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity

PCK1-mediated glycogenolysis facilitates ROS clearance and chemotherapy resistance in cervical cancer stem cells

Cervical cancer, one of the most common gynecological cancers, is primarily caused by human papillomavirus (HPV) infection. The development of resistance to chemotherapy is a significant hurdle in treatment. In this study, we investigated the mechanisms underlying chemoresistance in cervical cancer by focusing on the roles of glycogen metabolism and the pentose phosphate pathway (PPP). We employed the cervical cancer cell lines HCC94 and CaSki by manipulating the expression of key enzymes PCK1, PYGL, and GYS1, which are involved in glycogen metabolism, through siRNA transfection. Our analysis included measuring glycogen levels, intermediates of PPP, NADPH/NADP+ ratio, and the ability of cells to clear reactive oxygen species (ROS) using biochemical assays and liquid chromatography-mass spectrometry (LC-MS). Furthermore, we assessed chemoresistance by evaluating cell viability and tumor growth in NSG mice. Our findings revealed that in drug-resistant tumor stem cells, the enzyme PCK1 enhances the phosphorylation of PYGL, leading to increased glycogen breakdown. This process shifts glucose metabolism towards PPP, generating NADPH. This, in turn, facilitates ROS clearance, promotes cell survival, and contributes to the development of chemoresistance. These insights suggest that targeting aberrant glycogen metabolism or PPP could be a promising strategy for overcoming chemoresistance in cervical cancer. Understanding these molecular mechanisms opens new avenues for the development of more effective treatments for this challenging malignancy.

Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer

BACKGROUND

A greater emphasis has been placed on the part of cell cycle progression (CCP) in cancer in recent years. Nevertheless, the precise connection between CCP-related genes and bladder cancer (BCa) has remained elusive. This study endeavors to establish and validate a reliable risk model incorporating CCP-related factors, aiming to predict both the prognosis and immune landscape of BCa.

METHODS

Clinical information and RNA sequencing data were collected from the GEO and TCGA databases. Univariate and multivariate Cox regression analyses were conducted to construct a risk model associated with CCP. The performance of the model was assessed using ROC and Kaplan-Meier survival analyses. Functional enrichment analysis was employed to investigate potential cellular functions and signaling pathways. The immune landscape was characterized using CIBERSORT algorithms. Integration of the risk model with various clinical variables led to the development of a nomogram.

RESULTS

To build the risk model, three CCP-related genes (RAD54B, KPNA2, and TPM1) were carefully chosen. ROC and Kaplan-Meier survival analysis confirm that our model has good performance. About immunological infiltration, the high-risk group showed decreased levels of regulatory T cells and dendritic cells coupled with increased levels of activated CD4 + memory T cells, M2 macrophages, and neutrophils. Furthermore, the nomogram showed impressive predictive power for OS at 1, 3, and 5 years.

CONCLUSION

This study provides new insights into the association between the CCP-related risk model and the prognosis of BCa, as well as its impact on the immune landscape.

Development of a cell adhesion-based prognostic model for multiple myeloma: Insights into chemotherapy response and potential reversal of adhesion effects

Multiple myeloma (MM) is a hematologic malignancy notorious for its high relapse rate and development of drug resistance, in which cell adhesion-mediated drug resistance plays a critical role. This study integrated four RNA sequencing datasets (CoMMpass, GSE136337, GSE9782, and GSE2658) and focused on analyzing 1706 adhesion-related genes. Rigorous univariate Cox regression analysis identified 18 key prognosis-related genes, including KIF14, TROAP, FLNA, MSN, LGALS1, PECAM1, and ALCAM, which demonstrated the strongest associations with poor overall survival (OS) in MM patients. To comprehensively evaluate the impact of cell adhesion on MM prognosis, an adhesion-related risk score (ARRS) model was constructed using Lasso Cox regression analysis. The ARRS model emerged as an independent prognostic factor for predicting OS. Furthermore, our findings revealed that a heightened cell adhesion effect correlated with tumor resistance to DNA-damaging drugs, protein kinase inhibitors, and drugs targeting the PI3K/Akt/mTOR signaling pathway. Nevertheless, we identified promising drug candidates, such as tirofiban, pirenzepine, erlotinib, and bosutinib, which exhibit potential in reversing this resistance. In vitro, experiments employing NCIH929, RPMI8226, and AMO1 cell lines confirmed that MM cell lines with high ARRS exhibited poor sensitivity to the aforementioned candidate drugs. By employing siRNA-mediated knockdown of the key ARRS model gene KIF14, we observed suppressed proliferation of NCIH929 cells, along with decreased adhesion to BMSCs and fibronectin. This study presents compelling evidence establishing cell adhesion as a significant prognostic factor in MM. Additionally, potential molecular mechanisms underlying adhesion-related resistance are proposed, along with viable strategies to overcome such resistance. These findings provide a solid scientific foundation for facilitating clinically stratified treatment of MM.

Reactive Amine Functionalized Microelectrode Arrays Provide Short-Term Benefit but Long-Term Detriment to In Vivo Recording Performance

Intracortical microelectrode arrays (MEAs) are used for recording neural signals. However, indwelling devices result in chronic neuroinflammation, which leads to decreased recording performance through degradation of the device and surrounding tissue. Coating the MEAs with bioactive molecules is being explored to mitigate neuroinflammation. Such approaches often require an intermediate functionalization step such as (3-aminopropyl)triethoxysilane (APTES), which serves as a linker. However, the standalone effect of this intermediate step has not been previously characterized. Here, we investigated the effect of coating MEAs with APTES by comparing APTES-coated to uncoated controls in vivo and ex vivo. First, we measured water contact angles between silicon uncoated and APTES-coated substrates to verify the hydrophilic characteristics of the APTES coating. Next, we implanted MEAs in the motor cortex (M1) of Sprague-Dawley rats with uncoated or APTES-coated devices. We assessed changes in the electrochemical impedance and neural recording performance over a chronic implantation period of 16 weeks. Additionally, histology and bulk gene expression were analyzed to understand further the reactive tissue changes arising from the coating. Results showed that APTES increased the hydrophilicity of the devices and decreased electrochemical impedance at 1 kHz. APTES coatings proved detrimental to the recording performance, as shown by a constant decay up to 16 weeks postimplantation. Bulk gene analysis showed differential changes in gene expression between groups that were inconclusive with regard to the long-term effect on neuronal tissue. Together, these results suggest that APTES coatings are ultimately detrimental to chronic neural recordings. Furthermore, interpretations of studies using APTES as a functionalization step should consider the potential consequences if the final functionalization step is incomplete.

Dysregulated ANLN reveals immune cell landscape and promotes carcinogenesis by regulating the PI3K/Akt/mTOR pathway in clear cell renal cell carcinoma

Background

Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).

Methods

We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.

Results

Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.

Conclusions

These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a highly prevalent and fatal cancer. The role of PANoptosis, a novel form of programmed cell death, in HCC is yet to be fully understood. This study focuses on identifying and analyzing PANoptosis-associated differentially expressed genes in HCC (HPAN_DEGs), aiming to enhance our understanding of HCC pathogenesis and potential treatment strategies.

Methods

We analyzed HCC differentially expressed genes from TCGA and IGCG databases and mapped them to the PANoptosis gene set, identifying 69 HPAN_DEGs. These genes underwent enrichment analyses, and consensus clustering analysis was used to determine three distinct HCC subgroups based on their expression profiles. The immune characteristics and mutation landscape of these subgroups were evaluated, and drug sensitivity was predicted using the HPAN-index and relevant databases.

Results

The HPAN_DEGs were mainly enriched in pathways associated with the cell cycle, DNA damage, Drug metabolism, Cytokines, and Immune receptors. We identified three HCC subtypes (Cluster_1, SFN+PDK4-; Cluster_2, SFN-PDK4+; Cluster_3, SFN/PDK4 intermediate expression) based on the expression profiles of the 69 HPAN_DEGs. These subtypes exhibited distinct clinical outcomes, immune characteristics, and mutation landscapes. The HPAN-index, generated by machine learning using the expression levels of 69 HPAN_DEGs, was identified as an independent prognostic factor for HCC. Moreover, the high HPAN-index group exhibited a high response to immunotherapy, while the low HPAN-index group showed sensitivity to small molecule targeted drugs. Notably, we observed that the YWHAB gene plays a significant role in Sorafenib resistance.

Conclusion

This study identified 69 HPAN_DEGs crucial to tumor growth, immune infiltration, and drug resistance in HCC. Additionally, we discovered three distinct HCC subtypes and constructed an HPAN-index to predict immunotherapeutic response and drug sensitivity. Our findings underscore the role of YWHAB in Sorafenib resistance, presenting valuable insights for personalized therapeutic strategy development in HCC.