PRKCA Overexpression Is Frequent in Young Oral Tongue Squamous Cell Carcinoma Patients and Is Associated with Poor Prognosis

Identification of Molecular Subtypes and Prognostic Characteristics of Adrenocortical Carcinoma Based on Unsupervised Clustering

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a poor prognosis. Increasing evidence highlights the significant role of immune-related genes (IRGs) in ACC progression and immunotherapy, but the research is still limited. Based on the Cancer Genome Atlas (TCGA) database, immune-related molecular subtypes were identified by unsupervised consensus clustering. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression were employed to further establish immune-related gene signatures (IRGS). An evaluation of immune cell infiltration, biological function, tumor mutation burden (TMB), predicted immunotherapy response, and drug sensitivity in ACC patients was conducted to elucidate the applicative efficacy of IRGS in precision therapy. ACC patients were divided into two molecular subtypes through consistent clustering. Furthermore, the 3-gene signature (including PRKCA, LTBP1, and BIRC5) based on two molecular subtypes demonstrated consistent prognostic efficacy across the TCGA and GEO datasets and emerged as an independent prognostic factor. The low-risk group exhibited heightened immune cell infiltration, TMB, and immune checkpoint inhibitors (ICIs), associated with a favorable prognosis. Pathways associated with drug metabolism, hormone regulation, and metabolism were activated in the low-risk group. In conclusion, our findings suggest IRGS can be used as an independent prognostic biomarker, providing a foundation for shaping future ACC immunotherapy strategies.

Potential implications of protein kinase Cα in pathophysiological conditions and therapeutic interventions

PKCα is a molecule with many functions that play an important role in cell survival and death to maintain cellular homeostasis. Alteration in the normal functioning of PKCα is responsible for the complicated etiology of many pathologies, including cancer, cardiovascular diseases, kidney complications, neurodegenerative diseases, diabetics, and many others. Several studies have been carried out over the years on this kinase's function, and regulation in normal physiology and pathological conditions. A lot of data with antithetical results have therefore accumulated over time to create a complex framework of physiological implications connected to the PKCα function that needs comprehensive elucidation. In light of this information, we critically analyze the multiple roles played by PKCα in basic cellular processes and their molecular mechanism during various pathological conditions. This review further discusses the current approaches to manipulating PKCα signaling amplitude in the patient's favour and proposed PKCα as a therapeutic target to reverse pathological states.

Elucidating the role of missense SNP of protein kinase C epsilon in HCV-induced hepatocellular carcinoma

BACKGROUND

The protein kinase C (PKC) family of serine/threonine kinases contains more than ten isozymes that are involved in multiple signaling pathways, including cell cycle regulation and carcinogenesis. The PKCε isozyme is an oncogene known to be upregulated in various signaling pathways involved in hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC). However, there is no known association of missense SNPs in PKCε with this disease, which can be a potential biomarker for early diagnosis and treatment. This research reveals a novel missense SNP in PKCε that is associated with HCV-induced HCC in the Pakistani population.

METHODS

The PKCε SNP with amino acid substitution of E14K was chosen for wet lab analysis. Tetra ARMS-PCR was employed for the identification of high-risk SNP in PKCε of HCV-induced HCC patients. Liver function testing was also performed for comparison between the liver condition of the HCC patient and control group, and the viral load of HCC patient samples was evaluated to determine any alteration in the viral infectivity between different genotypes of the selected high-risk PKCε variant SNP.

RESULTS

Frequency distribution of the homozygous GG genotype was found to be highest among HCV-induced HCC patients and was also found to be significantly associated with disease development and progression. The p values of comparative data obtained for the other two genotypes, heterozygous AG and homozygous AA, of the SNP also showed the significance of the data for these alleles. Still, their odds ratio and relative risk analysis did not indicate their association with HCV-induced HCC.

CONCLUSION

The distribution of a genotype GG of PKCε has been found in HCV- induced HCC patients. Therefore, these PKCε SNP have the potential to be biomarkers for HCV-induced HCC. Further investigation using a larger sample size would provide additional insight into these initial data and open a new avenue for a better prognosis of this disease.

NCBP2 and TFRC are novel prognostic biomarkers in oral squamous cell carcinoma

There are few prognostic biomarkers and targeted therapeutics currently in use for the clinical management of oral squamous cell carcinoma (OSCC) and patient outcomes remain poor in this disease. A majority of mutations in OSCC are loss-of-function events in tumour suppressor genes that are refractory to conventional modes of targeting. Interestingly, the chromosomal segment 3q22-3q29 is amplified in many epithelial cancers, including OSCC. We hypothesized that some of the 468 genes located on 3q22-3q29 might be drivers of oral carcinogenesis and could be exploited as potential prognostic biomarkers and therapeutic targets. Our integrative analysis of copy number variation (CNV), gene expression and clinical data from The Cancer Genome Atlas (TCGA), identified two candidate genes: NCBP2, TFRC, whose expression positively correlates with worse overall survival (OS) in HPV-negative OSCC patients. Expression of NCBP2 and TFRC is significantly higher in tumour cells compared to most normal human tissues. High NCBP2 and TFRC protein abundance is associated with worse overall, disease-specific survival, and progression-free interval in an in-house cohort of HPV-negative OSCC patients. Finally, due to a lack of evidence for the role of NCBP2 in carcinogenesis, we tested if modulating NCBP2 levels in human OSCC cell lines affected their carcinogenic behaviour. We found that NCBP2 depletion reduced OSCC cell proliferation, migration, and invasion. Differential expression analysis revealed the upregulation of several tumour-promoting genes in patients with high NCBP2 expression. We thus propose both NCBP2 and TFRC as novel prognostic and potentially therapeutic biomarkers for HPV-negative OSCC.

Protein Kinase C (PKC) Isozymes as Diagnostic and Prognostic Biomarkers and Therapeutic Targets for Cancer

Protein kinase C (PKC) is a large family of calcium- and phospholipid-dependent serine/threonine kinases that consists of at least 11 isozymes. Based on their structural characteristics and mode of activation, the PKC family is classified into three subfamilies: conventional or classic (cPKCs; α, βI, βII, and γ), novel or non-classic (nPKCs; δ, ε, η, and θ), and atypical (aPKCs; ζ, ι, and λ) (PKCλ is the mouse homolog of PKCι) PKC isozymes. PKC isozymes play important roles in proliferation, differentiation, survival, migration, invasion, apoptosis, and anticancer drug resistance in cancer cells. Several studies have shown a positive relationship between PKC isozymes and poor disease-free survival, poor survival following anticancer drug treatment, and increased recurrence. Furthermore, a higher level of PKC activation has been reported in cancer tissues compared to that in normal tissues. These data suggest that PKC isozymes represent potential diagnostic and prognostic biomarkers and therapeutic targets for cancer. This review summarizes the current knowledge and discusses the potential of PKC isozymes as biomarkers in the diagnosis, prognosis, and treatment of cancers.

Overarching roles of diacylglycerol signaling in cancer development and antitumor immunity

Diacylglycerol (DAG) is a lipid second messenger that is generated in response to extracellular stimuli and channels intracellular signals that affect mammalian cell proliferation, survival, and motility. DAG exerts a myriad of biological functions through protein kinase C (PKC) and other effectors, such as protein kinase D (PKD) isozymes and small GTPase-regulating proteins (such as RasGRPs). Imbalances in the fine-tuned homeostasis between DAG generation by phospholipase C (PLC) enzymes and termination by DAG kinases (DGKs), as well as dysregulation in the activity or abundance of DAG effectors, have been widely associated with tumor initiation, progression, and metastasis. DAG is also a key orchestrator of T cell function and thus plays a major role in tumor immunosurveillance. In addition, DAG pathways shape the tumor ecosystem by arbitrating the complex, dynamic interaction between cancer cells and the immune landscape, hence representing powerful modifiers of immune checkpoint and adoptive T cell-directed immunotherapy. Exploiting the wide spectrum of DAG signals from an integrated perspective could underscore meaningful advances in targeted cancer therapy.

A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma

This study aimed to construct a signature of N⁶-methyladenosine (m6A) regulator-related genes that could be used for the prognosis of head and neck squamous cell carcinoma (HNSCC) and to clarify the molecular and immune characteristics and benefits of immune checkpoint inhibitor (ICI) therapy using the prognostic signature to define the subgroups of HNSCC. This study showed that eighteen m6A regulators were abnormally expressed in the Cancer Genome Atlas (TCGA) HNSCC tissues compared with those in normal tissues. We constructed a signature of 12 m6A regulator-related genes using the Cox risk model, combined with the least absolute shrinkage and selection operator (Lasso) variable screening algorithm. Based on the median of the signature risk score, the patients were divided into high- and low-risk groups. The Kaplan-Meier survival analyses showed that patients with high-risk scores demonstrated poorer overall survival (OS) than those with low-risk scores based on TCGA-HNSCC data (p <0.001). The OS of high-risk patients was significantly worse than that of low-risk patients in the GSE65858 (p <0.001) and International Cancer Genome Consortium (ICGC) oral cancer cohorts (p = 0.0089). Furthermore, immune infiltration analyses showed that 8 types of immune cell infiltration showed highly significant differences between the two risk groups (p <0.001). In the Imvigor210CoreBiologies dataset of patients who received ICIs, the objective response rate (ORR) of the low-risk group (32%) was significantly higher than that of the high-risk group (13%). Additionally, patients in the high-risk group presented with a more significant adverse OS than that of the low-risk group (p = 0.00032). GSE78220 also showed that the ORR of the low-risk group (64%) was higher than that of the high-risk group (43%) and the OS of low-risk patients was better than that of high-risk patients (p = 0.0064). The constructed prognostic signature, based on m6A regulator-related genes, could be used to effectively distinguish between prognoses for HNSCC patients. The prognostic signature was found to be related to the immune cell infiltration of HNSCC; it might help predict the responses and prognoses of ICIs during treatment.

Long noncoding RNA SNHG17: a novel molecule in human cancers

Many studies in recent years have found that dysregulation of long non-coding RNAs (lncRNAs) can contribute to disease. Small nucleolar RNA host gene 17 (SNHG17) is a novel cancer-related lncRNA of the SNHG family which is highly expressed in various tumors and may exert oncogenic functions. Several studies have demonstrated that SNHG17 is closely related to the proliferation, migration, invasion, apoptosis, and chemical drug resistance of tumor cells, and clinical studies have found an association between high SNHG17 expression and poor prognosis. In this review, we summarize relevant studies investigating SNHG17, focusing on its biological function as well as its potential value for clinical applications.