An integrated bioinformatic investigation of mitochondrial energy metabolism genes in colon adenocarcinoma followed by preliminary validation of CPT2 in tumor immune infiltration.

Background: The prognosis for colon adenocarcinoma (COAD) today remains poor. Changes in mitochondria-related genes and metabolic reprogramming are related to tumor growth, metastasis, and immune evasion and are key factors in tumor genesis and development. Methods: TCGA database was used to analyze the differentially expressed mitochondrial energy metabolism pathway-related genes (MMRGs) in COAD patients, and the mutation of MMRG in tumor cells, the biological processes involved, and the correlation with tumor immunity were also analyzed. Then, MMRG and MMRG-related genes were used to divide COAD patients into different subtypes, and immunocorrelation analysis and survival analysis were performed. Finally, univariate regression analysis and LASSO regression analysis were used to construct a prognostic risk model for COAD patients, which was verified by the GEO database and evaluated by Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves, and the correlation between the risk model and immunity and clinical subtypes based on MMRG was analyzed. Results: In this study, the MMRG patterns and tumor immune microenvironment characteristics in COAD patients were systematically evaluated by clustering the expression of 188 MMRGs. We identified two subtypes of COAD with different clinical and immunological characteristics. Eight of the 28 differentially expressed MMRG genes were used to construct risk scores. ROC and K-M curves suggested that the risk model could well predict the prognosis of COAD patients, and the risk model was related to immune cell infiltration and immune function. Conclusions: The two COAD subtypes identified by MMRG are helpful for the clinical differentiation of patients with different prognoses and tumor progressions, and the risk score can assist the clinical evaluation of patient prognosis. Our results suggest that CPT2 contributes to the recruitment and regulation of neutrophils in COAD. CPT2 may act as a valuable biomarker for COAD immunotherapy.

A Specific Predicting Model for Screening Skip Metastasis From Patients With Negative Central Lymph Nodes Metastasis in Papillary Thyroid Cancer.

Skip metastasis is a specific type of papillary thyroid cancer lymph node metastasis (LNM). The present study aimed to clarify the typical clinical characteristics of skip metastasis and optimize the prediction model, so as to provide a more individual treatment mode for skip metastasis. We retrospectively analyzed 1075 PTC patients with different lymph node metastasis statuses from two clinical centers. Comparisons have been made between patients with skip metastasis and other types of LNM. Univariate and multivariate analyses were performed to detect the risk factors for skip metastasis with negative LNM, and a nomogram for predicting skip metastasis was established. The rate of skip metastasis was 3.4% (37/1075). Compared with other types of LNM, significant differences showed in tumor size, upper portion location, thyroid capsular invasion, and ipsilateral nodular goiter with the central lymph node metastasis (CLNM) group, and in age and gender with the lateral lymph node metastasis (LLNM) group. Four variables were found to be significantly associated with skip metastasis and were used to construct the model: thyroid capsular invasion, multifocality, tumor size > 1 cm, and upper portion. The nomogram had good discrimination with a concordance index of 0.886 (95% confidence interval [CI], 0.823 to 0.948). In conclusion, the significant differences between skip metastasis and other types of LNM indicated that the lymph node drainage pathway of skip metastasis is different from either CLNM or LLNM. Furthermore, we established a nomogram for predicting risk of skip metastasis, which was able to effectively predict the potential risk of skip metastasis in patients without preoperative LNM clue.

Identification of Transcription Factor-Related Gene Signature and Risk Score Model for Colon Adenocarcinoma.

The prognosis of colon adenocarcinoma (COAD) remains poor. However, the specific and sensitive biomarkers for diagnosis and prognosis of COAD are absent. Transcription factors (TFs) are involved in many biological processes in cells. As the molecule of the signal pathway of the terminal effectors, TFs play important roles in tumorigenesis and development. A growing body of research suggests that aberrant TFs contribute to the development of COAD, as well as to its clinicopathological features and prognosis. In consequence, a few studies have investigated the relationship between the TF-related risk model and the prognosis of COAD. Therefore, in this article, we hope to develop a prognostic risk model based on TFs to predict the prognosis of patients with COAD. The mRNA transcription data and corresponding clinical data were downloaded from TCGA and GEO. Then, 141 differentially expressed genes, validated by the GEPIA2 database, were identified by differential expression analysis between normal and tumor samples. Univariate, multivariate and Lasso Cox regression analysis were performed to identify seven prognostic genes (E2F3, ETS2, HLF, HSF4, KLF4, MEIS2, and TCF7L1). The Kaplan-Meier curve and the receiver operating characteristic curve (ROC, 1-year AUC: 0.723, 3-year AUC: 0.775, 5-year AUC: 0.786) showed that our model could be used to predict the prognosis of patients with COAD. Multivariate Cox analysis also reported that the risk model is an independent prognostic factor of COAD. The external cohort (GSE17536 and GSE39582) was used to validate our risk model, which indicated that our risk model may be a reliable predictive model for COAD patients. Finally, based on the model and the clinicopathological factors, we constructed a nomogram with a C-index of 0.802. In conclusion, we emphasize the clinical significance of TFs in COAD and construct a prognostic model of TFs, which could provide a novel and reliable model for the prognosis of COAD.

Super-Enhancer Induced IL-20RA Promotes Proliferation/Metastasis and Immune Evasion in Colorectal Cancer.

Unveiling key oncogenic events in malignancies is the key to improving the prognosis and therapeutic outcome of malignancies. Lines of evidence have shown that super-enhancers control the expression of genes that determine the cell fate, but the oncogenic super-enhancers in colorectal cancer (CRC) and their impact on carcinogens remain largely unexplored. Here, we identified a new oncogenic super-enhancer-regulated gene, IL-20RA, in CRC. Using the integrative analysis of H3K27ac ChIP-seq and RNA-seq in CRC tumors and normal colon tissues, we obtained a series of oncogenic super-enhancers in CRC. We found that super-enhancer inhibition by JQ-1 or iBET-151 suppressed the growth of tumor cells and inhibited the expression of IL-20RA. We found that IL-20RA was highly expressed in the tumor tissue of CRC and related to the advanced stage. Further functional studies showed that knockdown of IL-20RA inhibited the growth and metastasis of CRC. In addition, we found that IL-20RA was involved in regulating oncogenic and immune pathways and affecting the expression of genes related to cell proliferation and immune evasion in CRC. Together, our study demonstrated a novel oncogene in CRC and shed new light on oncogenic super-enhancer contributions to cell proliferation and immune escape.