FABP5 suppresses colorectal cancer progression via mTOR-mediated autophagy by decreasing FASN expression

Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model

Background

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear.

Methods

ARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions.

Results

In our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies.

Conclusion

The predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

Microenvironmental changes in familial adenomatous polyposis during colorectal cancer carcinogenesis

Familial adenomatous polyposis (FAP) is a heritable disease that increases the risk of colorectal cancer (CRC) development because of heterozygous mutations in APC. Little is known about the microenvironment of FAP. Here, single-cell RNA sequencing was performed on matched normal tissues, adenomas, and carcinomas from four patients with FAP. We analyzed the transcriptomes of 56,225 unsorted single cells, revealing the heterogeneity of each cell type, and compared gene expression among tissues. Then we compared the gene expression with that of sporadic CRC. Furthermore, we analyzed specimens of 26 FAP patients and 40 sporadic CRC patients by immunohistochemistry. Immunosuppressiveness of myeloid cells, fibroblasts, and regulatory T cells was upregulated even in the early stages of carcinogenesis. CD8+ T cells became exhausted only in carcinoma, although the cytotoxicity of CD8+ T cells was gradually increased according to the carcinogenic step. When compared with those in the sporadic CRC microenvironment, the composition and function of each cell type in the FAP-derived CRC microenvironment had differences. Our findings indicate that an immunosuppressive microenvironment is constructed from a precancerous stage in FAP.

Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology

BACKGROUND

Colorectal Cancer (CRC) is a prevalent form of cancer, and the effectiveness of the main postoperative chemotherapy treatment, FOLFOX, varies among patients. In this study, we aimed to identify potential biomarkers for predicting the prognosis of CRC patients treated with FOLFOX through plasma proteomic characterization.

METHODS

Using a fully integrated sample preparation technology SISPROT-based proteomics workflow, we achieved deep proteome coverage and trained a machine learning model from a discovery cohort of 90 CRC patients to differentiate FOLFOX-sensitive and FOLFOX-resistant patients. The model was then validated by targeted proteomics on an independent test cohort of 26 patients.

RESULTS

We achieved deep proteome coverage of 831 protein groups in total and 536 protein groups in average for non-depleted plasma from CRC patients by using a Orbitrap Exploris 240 with moderate sensitivity. Our results revealed distinct molecular changes in FOLFOX-sensitive and FOLFOX-resistant patients. We confidently identified known prognostic biomarkers for colorectal cancer, such as S100A4, LGALS1, and FABP5. The classifier based on the biomarker panel demonstrated a promised AUC value of 0.908 with 93% accuracy. Additionally, we established a protein panel to predict FOLFOX effectiveness, and several proteins within the panel were validated using targeted proteomic methods.

CONCLUSIONS

Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC.

Global research trends and prospects of cellular metabolism in colorectal cancer

BACKGROUND

An increasing number of studies have focused on the role of cellular metabolism in the development of colorectal cancer (CRC). However, no work is currently available to synthesize the field through bibliometrics.

AIM

To analyze the development in the field of "glucose metabolism" (GM), "amino acid metabolism" (AM), "lipid metabolism" (LM), and "nucleotide metabolism" (NM) in CRC by visualization.

METHODS

Articles within the abovementioned areas of GM, AM, LM and NM in CRC, which were published from January 1, 1991, to December 31, 2022, are retrieved from the Web of Science Core Collection and analyzed by CiteSpace 6.2.R4 and VOSviewer 1.6.19.

RESULTS

The field of LM in CRC presented the largest number of annual publications and the fastest increase in the last decade compared with the other three fields. Meanwhile, China and the United States were two of the most prominent contributors in these four areas. In addition, Gang Wang, Wei Jia, Maria Notarnicola, and Cornelia Ulrich ranked first in publication numbers, while Jing-Yuan Fang, Senji Hirasawa, Wei Jia, and Charles Fuchs were the most cited authors on average in these four fields, respectively. "Gut microbiota" and "epithelial-mesenchymal transition" emerged as the newest burst words in GM, "gut microbiota" was the latest outburst word in AM, "metastasis", "tumor microenvironment", "fatty acid metabolism", and "metabolic reprogramming" were the up-to-date outbreaking words in LM, while "epithelial-mesenchymal transition" and "apoptosis" were the most recently occurring words in NM.

CONCLUSION

Research in "cellular metabolism in CRC" is all the rage at the moment, and researchers are particularly interested in exploring the mechanism to explain the metabolic alterations in CRC. Targeting metabolic vulnerability appears to be a promising direction in CRC therapy.

Modification patterns and metabolic characteristics of m6A regulators in digestive tract tumors

M6A is essential for tumor occurrence and progression. The expression patterns of m6A regulators differ in various kinds of tumors. Transcriptomic expression statistics together with clinical data from a database were analyzed to distinguish patients with digestive tract tumors. Based on the expression patterns of diverse m6A regulators, patients were divided into several clusters. Survival analysis suggested significant differences in patient prognosis among the m6A clusters. The results showed overlapping of m6A expression patterns with energy metabolism and nucleotide metabolism. Functional analyses imply that m6A modifications in tumor cells probably drive metabolic reprogramming to sustain rapid proliferation of cancer cells. Our analysis highlights the m6A risk characterizes various kinds of metabolic features and predicts chemotherapy sensitivity in digestive tract tumors, providing evidence for m6A regulators as markers to predict patient outcomes.

ALKBH5 enhances lipid metabolism reprogramming by increasing stability of FABP5 to promote pancreatic neuroendocrine neoplasms progression in an m6A-IGF2BP2-dependent manner

The process of post-transcriptional regulation has been recognized to be significantly impacted by the presence of N6-methyladenosine (m6A) modification. As an m6A demethylase, ALKBH5 has been shown to contribute to the progression of different cancers by increasing expression of several oncogenes. Hence, a better understanding of the key targets of ALKBH5 in cancer cells could potentially lead to the development of new therapeutic targets. However, the specific role of ALKBH5 in pancreatic neuroendocrine neoplasms (pNENs) remains largely unknown. Here, we demonstrated that ALKBH5 was up-regulated in pNENs and played a critical role in tumor growth and lipid metabolism. Mechanistically, ALKBH5 over-expression was found to increase the expression of FABP5 in an m6A-IGF2BP2 dependent manner, leading to disorders in lipid metabolism. Additionally, ALKBH5 was found to activate PI3K/Akt/mTOR signaling pathway, resulting in enhanced lipid metabolism and proliferation abilities. In conclusion, our study uncovers the ALKBH5/IGF2BP2/FABP5/mTOR axis as a mechanism for aberrant m6A modification in lipid metabolism and highlights a new molecular basis for the development of therapeutic strategies for pNENs treatment.