Investigating the effect of radiosensitizer for Ursolic Acid and Kamolonol Acetate ‌ on HCT-116 cell line

N6-methyladenosine methylation analysis of long noncoding RNAs and mRNAs in 5-FU-resistant colon cancer cells

N6 methyladenosine (m6A), methylation at the sixth N atom of adenosine, is the most common and abundant modification in mammalian mRNAs and non-coding RNAs. Increasing evidence shows that the alteration of m6A modification level could regulate tumour proliferation, metastasis, self-renewal, and immune infiltration by regulating the related expression of tumour genes. However, the role of m6A modification in colorectal cancer (CRC) drug resistance is unclear. Here, MeRIP-seq and RNA-seq techniques were utilized to obtain mRNA, lncRNA expression, and their methylation profiles in 5-Fluorouracil (5-FU)-resistant colon cancer HCT-15 cells and control cells. In addition, we performed detailed bioinformatics analysis as well as in vitro experiments of lncRNA to explore the function of lncRNA with differential m6A in CRC progression and drug resistance. In this study, we obtained the m6A methylomic landscape of CRC cells and resistance group cells by MeRIP-seq and RNA-seq. We identified 3698 differential m6A peaks, of which 2224 were hypermethylated, and 1474 were hypomethylated. Among the lncRNAs, 60 were hypermethylated, and 38 were hypomethylated. GO and KEGG analysis annotations showed significant enrichment of endocytosis and MAPK signalling pathways. Moreover, knockdown of lncRNA ADIRF-AS1 and AL139035.1 promoted CRC proliferation and invasive metastasis in vitro. lncRNA- mRNA network showed that ADIRF-AS1 and AL139035.1 May play a key role in regulating drug resistance formation. We provide the first m6A methylation profile in 5-FU resistance CRC cells and analyse the functions of differential m6A-modified mRNAs and lncRNAs. Our results indicated that differential m6A RNAs were significantly associated with MAPK signalling and endocytosis after induction of 5-FU resistance. Knockdown of LncRNA ADIRF-AS1 and AL139035.1 promotes CRC progression and might be critical in regulating drug resistance formation.

Curcumin inhibits the development of colorectal cancer via regulating the USP4/LAMP3 pathway

In this study, we aimed to explore the effects of curcumin on the progression of colorectal cancer and its underlying mechanisms involved. Cell proliferation, apoptosis and invasion were determined through CCK-8 assay, colony formation assay, EdU assay, flow cytometry, and transwell invasion assay, respectively. The protein expression of Bax, MMP2, USP4 and LAMP3 was measured using western blot. Pearson correlation coefficient was used to evaluate the relationship between USP4 and LAMP3. Co-IP was also conducted to determine the interaction between USP4 and LAMP3. Xenograft tumor model was established to explore the role of curcumin in colorectal cancer in vivo. IHC was utilized to measure the expression of Bax, MMP2, USP4 and LAMP3 in tumor tissues from mice. Curcumin significantly accelerated cell apoptosis, and inhibited cell proliferation and invasion in LoVo and HCT-116 cells. LAMP3 was augmented in colorectal cancer tissues and cells, and curcumin could reduce the expression of LAMP3. Curcumin decreased LAMP3 expression to exhibit the inhibition role in the progression of colorectal cancer. USP4 interacted with LAMP3, and positively regulated LAMP3 expression in colorectal cancer cells. LAMP3 overexpression could reverse the suppressive effects of USP4 knockdown on the development of colorectal cancer. Curcumin downregulated USP4 to impeded the progression of colorectal cancer via repressing LAMP3 expression. In addition, curcumin obviously restrained tumor growth in mice through downregulating USP4 and LAMP3 expression. These data indicated that curcumin exert the anti-tumor effects on the development of colorectal cancer through modulating the USP4/LAMP3 pathway.

LncRNA HCG18 affects diabetic cardiomyopathy and its association with miR-9-5p/IGF2R axis

This paper aimed to investigate the role of lncRNA HCG18 (HCG18) in the progression of diabetic cardiomyopathy (DCM) and potential mechanisms. Streptozocin (STZ) was used to induce DCM model in rats, which was confirmed by blood glucose concentration, body weight, and HE staining. Myocardial apoptosis was detected by TUNEL. H9c2 cardiomyocytes were used to construct cell models of DCM through treatment of high glucose. The results showed that HCG18 was overexpressed in STZ induced DCM rat model and high glucose induced H9c2 cardiomyocytes. Si-HCG18 significantly increased cell viability, reduced cell apoptosis, attenuated activities of myocardial enzymes and enhanced activities of antioxidant enzymes in STZ induced DM model and high glucose induced H9c2 cardiomyocytes, while the results of upregulation of HCG18, in high glucose induced H9c2 cardiomyocytes, were opposite with that of si-HCG18. MiR-9-5p was a target of HCG18, and which was down-regulated in cardiomyocytes of DCM. The overexpression of miR-9-5p could neutralize the high glucose induced cardiomyocyte injury, and the silence of miR-9-5p could reverse the effect of si-HCG18 on high glucose induced cardiomyocytes. MiR-9-5p could directly target to IGF2R, and IGF2R was overexpressed in cardiomyocytes of DCM. Up-regulation of IGF2R can reverse the protective effect of si-HCG18 on cardiomyocytes. Taken together, HCG18 is significantly increased in cardiomyocytes of DCM. Down-regulation of HCG18 can improve cardiomyocyte injury through miR-9-5p/IGF2R axis in DCM.

Machine learning identifies SLC6A14 as a novel biomarker promoting the proliferation and metastasis of pancreatic cancer via Wnt/β-catenin signaling

Pancreatic cancer (PC) has the poorest prognosis compared to other common cancers because of its aggressive nature, late detection, and resistance to systemic treatment. In this study, we aimed to identify novel biomarkers for PC patients and further explored their function in PC progression. We analyzed GSE62452 and GSE28735 datasets, identifying 35 differentially expressed genes (DEGs) between PC specimens and non-tumors. Based on 35 DEGs, we performed machine learning and identified eight diagnostic genes involved in PC progression. Then, we further screened three critical genes (CTSE, LAMC2 and SLC6A14) using three GEO datasets. A new diagnostic model was developed based on them and showed a strong predictive ability in screen PC specimens from non-tumor specimens in GEO, TCGA datasets and our cohorts. Then, clinical assays based on TCGA datasets indicated that the expression of LAMC2 and SLC6A14 was associated with advanced clinical stage and poor prognosis. The expressions of LAMC2 and SLC6A14, as well as the abundances of a variety of immune cells, exhibited a significant positive association with one another. Functionally, we confirmed that SLC6A14 was highly expressed in PC and its knockdown suppressed the proliferation, migration, invasion and EMT signal via regulating Wnt/β-catenin signaling pathway. Overall, our findings developed a novel diagnostic model for PC patients. SLC6A14 may promote PC progression via modulating Wnt/β-catenin signaling. This work offered a novel and encouraging new perspective that holds potential for further illuminating the clinicopathological relevance of PC as well as its molecular etiology.

Evaluation of BMP-2 as a Differentiating and Radiosensitizing Agent for Colorectal Cancer Stem Cells

BACKGROUND

Despite effective clinical responses, a large proportion of patients undergo resistance to radiotherapy. The low response rate to current treatments in different stages of colorectal cancer depends on the prominent role of stem cells in cancer.

OBJECTIVE

In the present study, the role of BMP-2 as an ionizing radiation-sensitive factor in colorectal cancer cells was investigated.

METHODS

A sphere formation assay was used for the enrichment of HCT-116 cancer stem cells (CSCs). The effects of combination therapy (BMP-2+ radiation) on DNA damage response (DDR), proliferation, and apoptosis were evaluated in HCT-116 and CSCs. Gene expressions of CSCs and epithelialmesenchymal transition (EMT) markers were also evaluated.

RESULTS

We found that the sphere formation assay showed a significant increase in the percentage of CSCs. Moreover, expression of CSCs markers, EMT-related genes, and DNA repair proteins significantly decreased in HCT-116 cells compared to the CSCs group after radiation. In addition, BMP-2 promoted the radiosensitivity of HCT-116 cells by decreasing the survival rate of the treated cells at 2, 4, and 6 Gy compared to the control group in HCT-116 cells.

CONCLUSION

Our findings indicated that BMP-2 could affect numerous signaling pathways involved in radioresistance. Therefore, BMP-2 can be considered an appealing therapeutic target for the treatment of radioresistant human colorectal cancer.

Sinapine thiocyanate exhibited anti-colorectal cancer effects by inhibiting KRT6A/S100A2 axis

Sinapine thiocyanate (ST), an alkaloid existed extensively in seeds of cruciferous plants, exhibits a number of pharmacological effects, including anti-inflammatory and anti-malignancy properties. However, it is still unknown what effects and molecular mechanisms ST has on colorectal cancer (CRC). In the current study, it was indicated that ST inhibited proliferation, colony formation, and apoptosis in vitro, as well as arrested the G1 phase of CRC cells. There was a significant repressive effects of ST on invasion and migration of CRC cells in vitro. RNA-sequencing indicated that 750 differentially expressed genes existed in CRC cells after ST treatment, and enrichment analysis demonstrated that ST obviously decreased the activation of keratinization pathways. Among DEGs enriched in keratinization, keratin 6A (KRT6A) was decreased the most significant, as well as its target gene S100 calcium-binding protein A2 (S100A2). Low expression of KRT6A and S100A2 signatures indicated a favorable prognosis in CRC patients. Moreover, we found overexpression of KRT6A relieved the inhibitory effects of ST in CRC cells. Furthermore, ST inhibited the CRC cell proliferation in vivo, and reduced KRT6A and KI67 expression in xenograft tumor. Taken together, we demonstrated that ST exhibited anti-CRC properties by inhibiting KRT6A/S100A2 axis. It is possible that ST can be used as a treatment for CRC.

Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation

Colorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.

Molecular mechanism of Danshenol C in reversing peritoneal fibrosis: novel network pharmacological analysis and biological validation

OBJECTIVE

The primary objective of this study is to elucidate the molecular mechanism underlying the reversal of peritoneal fibrosis (PF) by Danshenol C, a natural compound derived from the traditional Chinese medicine Salvia miltiorrhiza. By comprehensively investigating the intricate interactions and signaling pathways involved in Danshenol C's therapeutic effects on PF, we aim to unveil novel insights into its pharmacological actions. This investigation holds the potential to revolutionize the clinical application of Salvia miltiorrhiza in traditional Chinese medicine, offering promising new avenues for the treatment of PF and paving the way for evidence-based therapeutic interventions.

METHODS

Firstly, we utilized the YaTCM database to retrieve the structural formula of Danshenol C, while the SwissTargetPrediction platform facilitated the prediction of its potential drug targets. To gain insights into the genetic basis of PF, we acquired the GSE92453 dataset and GPL6480-9577 expression profile from the GEO database, followed by obtaining disease-related genes of PF from major disease databases. R software was then employed to screen for DEG associated with PF. To explore the intricate interactions between Danshenol C's active component targets, we utilized the String database and Cytoscape3.7.2 software to construct a PPI network. Further analysis in Cytoscape3.7.2 enabled the identification of core modules within the PPI network, elucidating key targets and molecular pathways critical to Danshenol C's therapeutic actions. Subsequently, we employed R to perform GO and KEGG pathway enrichment analyses, providing valuable insights into the functional implications and potential biological mechanisms of Danshenol C in the context of PF. To investigate the binding interactions between the core active components and key targets, we conducted docking studies using Chem3D, autoDock1.5.6, SYBYL2.0, and PYMOL2.4 software. We applied in vivo and in vitro experiments to prove that Danshenol C can improve PF. In order to verify the potential gene and molecular mechanism of Danshenol C to reverse PF, we used quantitative PCR, western blot, and apoptosis, ensuring robust and reliable verification of the results.

RESULTS

① Wogonin, sitosterol, and Signal Transducer and Activator of Transcription 5 (STAT5) emerged as the most significant constituents among the small-molecule active compounds and gene targets investigated. ②38 targets intersected with the disease, among which MAPK14, CASP3, MAPK8 and STAT3 may be the key targets; The results of GO and KEGG analysis showed that there was a correlation between inflammatory pathway and Apoptosis. ④Real-time PCR showed that the mRNA expressions of MAPK8 (JNK1), MAPK14 (P38) and STAT3 were significantly decreased after Danshenol C treatment (P < 0.05), while the mRNA expression of CASP3 was significantly increased (P < 0.05)⑤Western blot showed that protein expressions of CASP3 and MAPK14 were significantly increased (P < 0.05), while the expression of STAT3 and MAPK8 was decreased after Danshenol C treatment (P < 0.05). ⑥There was no significant difference in flow analysis of apoptosis among groups.

CONCLUSION

The findings suggest that Danshenol C may modulate crucial molecular pathways, including the MAPK, Apoptosis, Calcium signaling, JAK-STAT signaling, and TNF signaling pathways. This regulation is mediated through the modulation of core targets such as STAT3, MAPK14, MAPK8, CASP3, and others. By targeting these key molecular players, Danshenol C exhibits the potential to regulate cellular responses to chemical stress and inflammatory stimuli. The identification of these molecular targets and pathways represents a significant step forward in understanding the molecular basis of Danshenol C's therapeutic effects in PF. This preliminary exploration provides novel avenues for the development of anti-PF treatment strategies and the discovery of potential therapeutic agents. By targeting specific core targets and pathways, Danshenol C opens up new possibilities for the development of more effective and targeted drugs to combat PF. These findings have the potential to transform the landscape of PF treatment and offer valuable insights for future research and drug development endeavors.

Identification of the therapeutic mechanism of the saffron crocus on glioma through network pharmacology and bioinformatics analysis

Saffron crocus is a herbal medicine of traditional Tibetan medicine (TTM). Saffron extract has been indicated to inhibit tumor cell growth and promote tumor cell apoptosis in a variety of cancers, including glioma, but the specific mechanism is not clear. To study the possible mechanism of saffron action on glioma, network pharmacology and bioinformatics analysis methods were used in this study. We used the online database to obtain the active ingredients of saffron and their targets. Glioma-related targets were also acquired from online database. We intersected drug targets with glioma-related targets and conducted PPI network analysis to obtain network core genes. Then, we obtained RNA-seq data from The Cancer Genome Atlas (TCGA) database for glioma patients. Through different expression analysis and lasso regression, further screening of core genes in the network was conducted, and a prognostic model was established. The sample was divided into two groups with high and low risk using this model. The RNA-seq data from the Chinese Glioma Genome Atlas (CGGA) database were used to further validate our prediction model. Then, we explored the difference in pathways enrichment between high-risk patients and low-risk patients and calculated the difference in immune microenvironment between the two groups. Finally, we used scRNA-seq data in the CGGA database to analyze the cell types in which the model gene is mainly enriched and predicted the cell types which saffron effected on.

Identification of Novel Biomarkers for Response to Preoperative Chemoradiation in Locally Advanced Rectal Cancer with Genetic Algorithm-Based Gene Selection

BACKGROUND

The conventional treatment for patients with locally advanced colorectal tumors is preoperative chemo-radiotherapy (PCRT) preceding surgery. This treatment strategy has some long-term side effects, and some patients do not respond to it. Therefore, an evaluation of biomarkers that may help predict patients' response to PCRT is essential.

METHODS

We took advantage of genetic algorithm to search the space of possible combinations of features to choose subsets of genes that would yield convenient performance in differentiating PCRT responders from non-responders using a logistic regression model as our classifier.

RESULTS

We developed two gene signatures; first, to achieve the maximum prediction accuracy, the algorithm yielded 39 genes, and then, aiming to reduce the feature numbers as much as possible (while maintaining acceptable performance), a 5-gene signature was chosen. The performance of the two gene signatures was (accuracy = 0.97 and 0.81, sensitivity = 0.96 and 0.83, and specificity = 86 and 0.77) using a logistic regression classifier. Through analyzing bias and variance decomposition of the model error, we further investigated the involved genes by discovering and validating another 28-gene signature which possibly points towards two different sub-systems involved in the response of the patients to treatment.

CONCLUSIONS

Using genetic algorithm as our gene selection method, we have identified two groups of genes that can differentiate PCRT responders from non-responders in patients of the studied dataset with considerable performance.

IMPACT

After passing standard requirements, our gene signatures may be applicable as a robust and effective PCRT response prediction tool for colorectal cancer patients in clinical settings and may also help future studies aiming to further investigate involved pathways gain a clearer picture for the course of their research.

Tumor cell-derived exosomes regulate macrophage polarization: Emerging directions in the study of tumor genesis and development

As an extracellular vesicle, exosomes play an important role in intercellular information transmission, delivering cargos of the parent cell, such as RNA, DNA, proteins, and lipids, activating different signaling pathways in the target cell and regulating inflammation, angiogenesis, and tumor progression. In particular, exosomes secreted by tumor cells can change the function of surrounding cells, creating a microenvironment conducive to tumor growth and metastasis. For example, after macrophages phagocytose exosomes and accept their cargos, they activate macrophage polarization-related signaling pathways and polarize macrophages into M1 or M2 types to exert antitumor or protumor functions. Currently, the study of exosomes affecting the polarization of macrophages has attracted increasing attention. Therefore, this paper reviews relevant studies in this field to better understand the mechanism of exosome-induced macrophage polarization and provide evidence for exploring novel targets for tumor therapy and new diagnostic markers in the future.

TGM2, HMGA2, FXYD3, and LGALS4 genes as biomarkers in acquired oxaliplatin resistance of human colorectal cancer: A systems biology approach

Acquired resistance to oxaliplatin is considered as the primary reason for failure in colorectal cancer (CRC) therapy. Identifying the underlying resistance mechanisms may improve CRC treatment. The present study aims to identify the key genes involved in acquired oxaliplatin-resistant in CRC by confirming the oxaliplatin resistance index (OX-RI). To this aim, two public microarray datasets regarding oxaliplatin-resistant CRC cells with different OX-RI, GSE42387, and GSE76092 were downloaded from GEO database to identify differentially expressed genes (DEGs). The results indicated that the OX-RI affects the gene expression pattern significantly. Then, 54 common DEGs in both datasets including 18 up- and 36 down-regulated genes were identified. Protein-protein interaction (PPI) analysis revealed 13 up- (MAGEA6, TGM2, MAGEA4, SCHIP1, ECI2, CD33, AKAP12, MAGEA12, CALD1, WFDC2, VSNL1, HMGA2, and MAGEA2B) and 12 down-regulated (PDZK1IP1, FXYD3, ALDH2, CEACAM6, QPRT, GRB10, TM4SF4, LGALS4, ALDH3A1, USH1C, KCNE3, and CA12) hub genes. In the next step, two novel up-regulated hub genes including ECI2 and SCHIP1 were identified to be related to oxaliplatin resistance. Functional enrichment and pathway analysis indicated that metabolic pathways, proliferation, and epithelial-mesenchymal transition may play dominant roles in CRC progression and oxaliplatin resistance. In the next procedure, two in vitro oxaliplatin-resistant sub-lines including HCT116/OX-R4.3 and HCT116/OX-R10 cells with OX-IR 3.93 and 10.06 were established, respectively. The results indicated the up-regulation of TGM2 and HMGA2 in HCT116/OX-R10 cells with high OX-RI and down-regulation of FXYD3, LGALS4, and ECI2 in both cell types. Based on the results, TGM2, HMGA2, FXYD3, and LGALS4 genes are related to oxaliplatin-resistant CRC and may serve as novel therapeutic targets.

Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module. Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes. In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.

Identification of key genes in colorectal cancer diagnosis by co-expression analysis weighted gene co-expression network analysis

BACKGROUND

The purpose of this study was using bioinformatics tools to identify biomarkers and molecular factors involved in the diagnosis of colorectal cancer, which are effective for the diagnosis and treatment of the disease.

METHODS

We determined differentially expressed genes (DEGs) related to colorectal cancer (CRC) using the data series retrieved from GEO database. Then the weighted gene co-expression network analysis (WGCNA) was conducted to explore co-expression modules related to CRC diagnosis. Next, the relationship between the integrated modules with clinical features such as the stage of CRC was evaluated. Other downstream analyses were performed on selected module genes.

RESULTS

In this study, after performing the WGCNA method, a module named blue module which was more significantly associated with the CRC stage was selected for further evaluation. Afterward, the Protein-protein interaction network through sting software for 154 genes of the blue module was constructed and eight hub genes were identified through the evaluation of constructed network with Cytoscape. Among these eight hub genes, upregulation of MMP9, SERPINH1, COL1A2, COL5A2, COL1A1, SPARC, and COL5A1 in CRC was validated in other microarray and TCGA data. Based on the results of the mRNA-miRNA interaction network, SERPINH1 was found as a target gene of miR-940. Finally, results of the DGIDB database indicated that Andecaliximab, Carboxylated glucosamine, Marimastat, Tozuleristide, S-3304, Incyclinide, Curcumin, Prinomastat, Demethylwedelolactone, and Bevacizumab, could be used as a therapeutic agent for targeting the MMP9. Furthermore, Ocriplasmin and Collagenase clostridium histolyticum could target COL1A1, COL1A2, COL5A1, and COL5A2.

CONCLUSION

Taken together, the results of the current study indicated that seven hub genes including COL1A2, COL5A1, COL5A2, SERPINH1, MMP9, SPARC, and COL1A1 which were upregulated in CRC could be used as a diagnostic and progression biomarker of CRC. On the other hand, miR-940 which targets SERPINH1 could be used as a potential biomarker of CRC. More ever, Andecaliximab, Carboxylated glucosamine, Marimastat, Tozuleristide, S-3304, Incyclinide, Curcumin, Prinomastat, Demethylwedelolactone, Bevacizumab, Ocriplasmin , and Collagenase clostridium histolyticum were introduced as therapeutic agents for CRC which their therapeutic potential should be evaluated experimentally.

Investigating the role of peptides in effective therapies against cancer

Early diagnosis and effective treatment of cancer are challenging. To diagnose and treat cancer effectively and to overcome these challenges, fundamental innovations in traditional diagnosis and therapy are necessary. Peptides can be very helpful in this regard due to their potential and diversity. To enhance the therapeutic potential of peptides, their limitations must be properly identified and their structures engineered and modified for higher efficiency. Promoting the bioavailability and stability of peptides is one of the main concerns. Peptides can also be effective in different areas of targeting, alone or with the help of other therapeutic agents. There has been a lot of research in this area, and the potential for variability of peptides will continue to improve this process. Another promising area in which peptides can help treat cancer is peptide vaccines, which are undergoing promising research, and high throughput technologies can lead to fundamental changes in this area. Peptides have been effective in almost all areas of cancer treatment, and some have even gone through clinical phases. However, many barriers need to be overcome to reach the desired point. The purpose of this review is to evaluate the mechanisms associated with peptides in the diagnosis and treatment of cancer. Therefore, related studies in this area will be discussed.

Ganoderic acid T improves the radiosensitivity of HeLa cells via converting apoptosis to necroptosis

The use of natural substances derived from traditional Chinese medicine and natural plants as safe radiosensitizing adjuvants is a new trend for cancer radiotherapy. Ganoderma lucidum has been used as a traditional Chinese medicine with a history of more than 2000 years. Ganoderic acid T (GAT) is a typical triterpene of G. lucidum, which has strong cytotoxicity to cancer cells, but whether it has radiation sensitization effect has not been explored. In this work, we treated the HeLa cells with different concentrations of GAT before exposure to gamma-ray radiation and investigated its influence on the radiosensitivity. The cell viability, apoptosis rate, necoptosis rate, intracellular ATP level, cell cycle, the amount of H2AX and 53BP1, reactive oxygen species, and mitochondrial membrane potential were examined. Apoptotic, necroptotic, and autophagic biomarker proteins, including caspase 8, cytochrome c, caspase 3, RIPK, MLKL, P62, and LC3, were analyzed. As a result, we confirmed that with treatment of GAT, the gamma-ray radiation induced both apoptosis and necroptosis in HeLa cells, and with increase of GAT, the percentage ratio of necroptosis was increased. The involved pathways and mechanisms were also explored and discussed.