Metabolism-Based Molecular Subtyping Endows Effective Ketogenic Therapy in p53-Mutant Colon Cancer

A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma: A 16-year prospective multicentric study

Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments.

Comparative Expression Analysis of TP53 Tumor Suppressor and MDM2 Oncogene in Colorectal Adenocarcinoma

Background/Aim

The tumor protein 53 (TP53) tumor suppressor protein (17p13.1) acts as a significant regulator for the cell cycle normal function. The gene is frequently mutated in colorectal adenocarcinoma (CRC) patients and is associated to poor prognosis and low response rates to chemo-targeted therapy. Our purpose was to correlate TP53 expression with Mouse Double Minute 2 Homolog (MDM2), a proto-oncogene (12q14.3) and a major negative regulator in the TP53-MDM2 auto-regulatory pathway.

Materials and Methods

A total of forty (n=40) colorectal adenocarcinoma (CRC) cases were included in this study. An immunohistochemistry-based assay was implemented by using anti-TP53 and anti-MDM2 antibodies in the corresponding tissue sections. Additionally, a digital image analysis assay was implemented for objectively measuring TP53/MDM2 immunostaining intensity levels.

Results

TP53 protein overexpression was detected in 27/40 (67.5%), whereas MDM2 overexpression in 28/40 (70%) cases. Interestingly, in 21/40 (52.5%) cases, a combined TP53/MDM2 co-expression was detected, whereas in 6/40 (15%), a combined loss of expression was identified (overall co-expression: p=0.119). p53 overexpression was significantly correlated to grade of the examined cases (p=0.001), whereas MDM2 to stage and max diameter of the malignancies (p=0.001 and 0.024, respectively).

Conclusion

TP53/MDM2 over expression is a frequent and significant genetic event in CRCs associated with an aggressive biological behavior, as a result of increased dedifferentiation grade and advanced stage/elevated tumor volume, respectively. MDM2 oncogene overactivation combined with mutated and overexpressed TP53 is observed in sub-groups of patients leading to specific gene/protein signatures - targets for personalized chemotherapeutic approaches.

Aldose reductase and cancer metabolism: The master regulator in the limelight

It is strongly established that metabolic reprogramming mediates the initiation, progression, and metastasis of a variety of cancers. However, there is no common biomarker identified to link the dysregulated metabolism and cancer progression. Recent studies strongly advise the involvement of aldose reductase (AR) in cancer metabolism. AR-mediated glucose metabolism creates a Warburg-like effect and an acidic tumour microenvironment in cancer cells. Moreover, AR overexpression is associated with the impairment of mitochondria and the accumulation of free fatty acids in cancer cells. Further, AR-mediated reduction of lipid aldehydes and chemotherapeutics are involved in the activation of factors promoting proliferation and chemo-resistance. In this review, we have delineated the possible mechanisms by which AR modulates cellular metabolism for cancer proliferation and survival. An in-depth understanding of cancer metabolism and the role of AR might lead to the use of AR inhibitors as metabolic modulating agents for the therapy of cancer.

Application of lncRNA-miRNA-mRNA ceRNA network analysis in the treatment of androgenic alopecia

BACKGROUND

Long noncoding RNAs (lncRNAs) can be used as competitive endogenous RNAs (ceRNAs) to bind to microRNAs (miRNAs) to regulate gene expression. Previous studies have demonstrated that ceRNAs play an important role in the development of tumors. However, it is not clear whether the lncRNA-miRNA-mRNA ceRNA network plays a role in androgenic alopecia (AGA).

METHODS

The hair follicles of three AGA patients and three healthy individuals were collected for high-throughput whole transcriptome sequencing to screen for differentially expressed lncRNAs. Differentially expressed lncRNA target genes were subjected to databases to predict miRNA-mRNA and lncRNA-miRNA relationship pairs, and a ceRNA network was constructed using Cytoscape software. Relative expression was verified by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

RESULTS

84 lncRNAs were significantly differentially expressed between the hair follicles of AGA patients and those of healthy individuals; 30 were upregulated, and 54 were downregulated. The top 10 upregulated lncRNAs were ENST00000501520, ENST00000448179, ENST00000318291, ENST00000568280, ENST00000561121, ENST00000376609, ENST00000602414, ENST00000573866, ENST00000513358, and ENST00000564194. The top 10 downregulated lncRNAs were ENST00000566804, ENST00000561973, ENST00000587680, ENST00000569927, ENST00000340444, ENST00000424345, ENST00000589787, NR_024344, NR_073026, and NR_110001. The qRT-PCR validation results and receiver-operating characteristic curve analysis indicated that one upregulated lncRNA, LOXL1-AS1 (ENST00000564194), had the most significant clinical diagnostic potential. After further analysis, it was concluded that LOXL1-AS1 could be used as a sponge to target hsa-miR-5193, thereby regulating TP53 expression.

CONCLUSION

The ceRNA network-regulating AGA was constructed through high-throughput sequencing. Our study also identified a key lncRNA that is possibly related to the AGA pathological process.