Prognosis biomarker and potential therapeutic target CRIP2 associated with radiosensitivity in NSCLC cells

Recent advances progress of targeted drugs combined with radiotherapy for advanced non-small cell lung cancer: a review

Targeted drug therapy plays an important role in the clinical application of non-small cell lung cancer, especially adenocarcinoma. However, for patients with advanced disease, drug resistance after targeted therapy, unclear target, and other reasons that cannot or do not want surgery, the combination of chemotherapy, radiotherapy, immunity, etc. is often used. The synergistic effect of targeted drugs and radiotherapy in non-small cell lung cancer has shown good clinical efficacy. This article reviews the clinical progress of targeted drug therapy combined with radiotherapy in advanced non-small cell lung cancer in recent years, in order to provide new ideas for further clinical research of this treatment mode.

[Radioproteomics for Discriminating the Activity and Inactivity of Immune Checkpoint Molecules in Breast Cancer]

PURPOSE

Radioproteomics studies investigating the relationship between lesion phenotype and proteins have been progressed. The purpose of this study was to develop a radioproteomics method for discriminating between active and inactive immune checkpoint molecules based on lesion phenotype.

METHODS

From the public database TCGA-BRCA, mRNA and fat suppression contrast-enhanced T1-weighted images of 49 patients with breast cancer were selected for the experiment. Using mRNA, we defined cases with active (10 cases) and inactive (39 cases) immune checkpoint molecules. To discriminate these cases using lesion phenotype, 275 radiomics features were measured from the tumor area. After selecting 3 radiomics features by using Lasso, logistic regression was employed to discriminate between active and inactive cases of immune checkpoint molecules.

RESULTS

Evaluation of ROC analysis showed that the AUC was 0.81.

CONCLUSION

Patients whose immune cell function is being braked by immune checkpoint molecules are likely to respond to immune checkpoint inhibitors when their activity is inhibited. Therefore, our results may be applied to predict the effects of immune checkpoint inhibitors in breast cancer treatment.

131I-Caerin 1.1 and 131I-Caerin 1.9 for the treatment of non-small-cell lung cancer

Objective

To investigate the effect of the ¹³¹I-labeled high-affinity peptides Caerin 1.1 and Caerin 1.9 for the treatment of A549 human NSCLC cells.

Methods

① 3-[4,5-Dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) and plate clone formation assays were performed to confirm the in vitro anti-tumor activity of Caerin 1.1 and Caerin 1.9. ② Chloramine-T was used to label Caerin 1.1 and Caerin 1.9 with ¹³¹I, and the Cell Counting Kit 8 assay was performed to analyze the inhibitory effect of unlabeled Caerin 1.1, unlabeled Caerin 1.9, ¹³¹I-labeled Caerin 1.1, and ¹³¹I-labeled Caerin 1.9 on the proliferation of NSCLC cells. An A549 NSCLC nude mouse model was established to investigate the in vivo anti-tumor activity of unlabeled Caerin 1.1, unlabeled Caerin 1.9, ¹³¹I-labeled Caerin 1.1, and ¹³¹I-labeled Caerin 1.9.

Results

① Caerin 1.1 and Caerin 1.9 inhibited the proliferation of NSCLC cells in vitro in a concentration-dependent manner. The half-maximal inhibitory concentration was 16.26 µg/ml and 17.46 µg/ml, respectively, with no significant intergroup difference (P>0.05). ② ¹³¹I-labeled Caerin 1.1 and ¹³¹I-labeled Caerin 1.9 were equally effective and were superior to their unlabeled versions in their ability to inhibit the proliferation and growth of NSCLC cells (P>0.05).

Conclusions

¹³¹I-labeled Caerin 1.1 and ¹³¹I-labeled Caerin 1.9 inhibit the proliferation and growth of NSCLC cells and may become potential treatments for NSCLC.

Based on Molecular Subtypes, Immune Characteristics and Genomic Variation to Constructing and Verifying Multi-Gene Prognostic Characteristics of Colorectal Cancer

Background: Colon cancer (COAD) has been identified as being among the most prevalent tumors globally and ranked the third major contributor to cancer-related mortality. COAD is a molecularly heterogeneous disease. There are great differences in clinical manifestations and prognosis among different molecular subtypes.

Methods:379 TCGA-COAD samples were divided into four subtypes: primary proliferative, with collective, crypt-like, and EMT invasion. The differences among the four subtypes were analyzed from the multidimensional perspectives of immunity, genomic variation, and prognosis. The limma package was utilized to identify differentially expressed genes (DEGs) amongst different molecular subtypes. Phenotype-related coexpressed gene modules were identified using WGCNA. The polygenic prognosis model was created utilizing the lasso Cox analysis and verified by time-dependent subject operating characteristics (ROC).

Results: There are some differences in prognosis, TMB and common gene variation, immune score, and immunotherapy/chemotherapy between proliferative and three invasive molecular subtypes. 846 differential genes (DEGs) were obtained by limma packet analysis. Differential gene analysis was utilized to screen the DEGs among distinct subtypes, which were significantly enriched in the pathways related to tumorigenesis and development. Co-expression network analysis found 46 co-expressed genes correlated with proliferative and three invasive phenotypes. Based on differentially co-expressed genes, we developed a prognostic risk model of 8-genes signature, which exhibited strong stability regardless of external and internal validation. RT-PCR experiments proved the expression of eight genes in tumor and normal samples.

Conclusion: We have developed an eight-gene signature prognostic stratification system. Furthermore, we proposed that this classifier can serve as a molecular diagnostic tool to assess the prognosis of colon cancer patients.