Triphala is an Ayurvedic rasayana formulation reputed for its antitumour activities, and chebulinic acid and chebulagic acid, along with other phenolic acids, have been proposed to be responsible for its effects. In this study, the anti-proliferative activities of these agents were evaluated in colorectal carcinoma cell lines with three phenotypes exposed to several batches of triphala samples with different quantities of chebulinic acid and chebulagic acid. The pro-apoptotic and anti-migratory activities and the probable antitumour mechanisms of the more potent anti-proliferative phytochemical were also investigated. The results demonstrated that chebulinic acid, which exerts potent anti-proliferative, pro-apoptotic and anti-migratory effects, is a key molecule for maintaining the antitumour efficacy of triphala. The antitumour mechanism of chebulinic acid is probably related to the PI3K/AKT and MAPK/ERK pathways. Chebulinic acid is not only a critical component of the anticancer activities of triphala but also a promising natural multi-target antitumour agent with therapeutic potential.

This research aimed to investigate the anti-tumor effects and underlying genetic mechanisms of herbal medicine Triphala (TRP) in oral squamous cell carcinoma (OSCC). The target genes of Triphala (TRP) in oral squamous cell carcinoma (OSCC) were identified, and subsequent functional enrichment analysis was conducted to determine the enriched signaling pathways. Based on these genes, a protein-protein interaction network was constructed to identify the top 10 genes with the highest degree. Genes deregulated in OSCC tumor samples were identified to be hub genes among the top 10 genes. In vitro experiments were performed to investigate the influence of TRP extracts on the cell metabolic activity, migration, invasion, apoptosis, and proliferation of two OSCC cell lines (CAL-27 and SCC-9). The functional rescue assay was conducted to investigate the effect of applying the inhibitor and activator of an enriched pathway on the phenotypes of cancer cells. In addition, the zebrafish xenograft tumor model was established to investigate the influence of TRP extracts on tumor growth and metastasis in vivo. The target genes of TRP in OSCC were prominently enriched in the PI3K-Akt signaling pathway, with the identification of five hub genes (JUN, EGFR, ESR1, RELA, and AKT1). TRP extracts significantly inhibited cell metabolic activity, migration, invasion, and proliferation and promoted cell apoptosis in OSCC cells. Notably, the application of TRP extracts exhibited the capacity to downregulate mRNA and phosphorylated protein levels of AKT1 and ESR1, while concomitantly inducing upregulation of mRNA and phosphorylated protein levels in the remaining three hub genes (EGFR, JUN, and RELA). The functional rescue assay demonstrated that the co-administration of TRP and the PI3K activator 740Y-P effectively reversed the impact of TRP on the phenotypes of OSCC cells. Conversely, the combination of TRP and the PI3K inhibitor LY294002 further enhanced the effect of TRP on the phenotypes of OSCC cells. Remarkably, treatment with TRP in zebrafish xenograft models demonstrated a significant reduction in both tumor growth and metastatic spread. Triphala exerted significant inhibitory effects on cell metabolic activity, migration, invasion, and proliferation in OSCC cell lines, accompanied by the induction of apoptosis, which was mediated through the inactivation of the PI3K/Akt pathway.

Objectives. Triphala is a herbal medicine that has been widely used for treating a variety of ailments. This study aims to systematically analyze the antitumor effects of Triphala on gynecological cancers. Methods. The antineoplastic activities of Triphala on gynecological cancers were analyzed using network pharmacology-based strategies. Afterward, the human ovarian cancer cell line SK-OV-3, cervical cancer cell line HeLa, and endometrial cancer cell line HEC-1-B were selected for experimetal valification. Results. Network pharmacology analysis suggested that Triphala could comprehensively intervene in proliferation and apoptosis through diverse signaling pathways, mainly including MAPK/ERK, PI3K/Akt/mTOR, and NF-κB/p53. The Cell Counting Kit 8 (CCK-8) assay illustrated that Triphala was able to inhibit cell proliferation with half inhibition concentration (IC₅₀) values of 98.28 ± 13.71, 95.56 ± 8.94, and 101.23 ± 7.76 µg/mL against SK-OV-3, HeLa, and HEC-1-B cells, respectively. The ELISA experiment demonstrated that Triphala was capable of promoting programmed cell death, with dosage correlations. The antiproliferative and proapoptotic activities were confirmed by flow cytometric analysis using Ki67 antibody and Annexin V/propidium iodide (PI) dual staining. Western blotting revealed a decrease in expression levels of phospho-Akt, phospho-p44/42, and phospho-NF-κB p56 in cells administered Triphala, which indicated that the possible mechanism could involve downregulation of MAPK/ERK, PI3K/Akt/mTOR, and NF-κB/p53 signaling pathways, as was predicted. Conclusion. Triphala holds great promise for treating gynecological cancers. Although the favorable pharmacological properties have been preliminarily investigated in this study, further studies are still needed to uncover the sophisticated mechanism of Triphala in cancer therapy.

Objectives. Triphala is an extensively prescribed traditional medicinal formula with potential therapeutic effects on various malignancies such as breast, colon, pancreas, prostate, ovarian, cervical, endometrial, and lymphatic cancer as well as melanoma. This study aimed to investigate Triphala for antitumor activities against gastric cancers. Methods. In vitro tumor growth and migration of human gastric cancer cells were examined using the CCK-8 and Transwell assays, respectively. In vivo tumor progression was studied in a zebrafish xenograft model. The anticancer activity of Triphala was quantified as growth and metastasis inhibition rate. The underlying molecular mechanism was investigated by Western blotting. Results. The CCK-8 and Transwell experiments indicated that Triphala significantly decreased tumor proliferation and suppressed cell migration in vitro. The zebrafish xenograft study revealed that administration of Triphala inhibited the xenograft growth and metastasis of transplanted carcinoma cells in vivo. Western blotting analysis demonstrated an inhibition of phosphorylation of EGFR, Akt, and ERK in the presence of Triphala, indicating that its antineoplastic mechanism is associated with the regulation of the EGFR/Akt/ERK signaling cascade. Conclusion. Triphala is a promising antineoplastic agent for the treatment of gastric carcinomas with significant antiproliferative and antimetastatic activities.

Alzheimer's disease (AD) is an age-related neurodegenerative disease with unknown mechanism that is characterized by the aggregation of abnormal proteins and dysfunction of immune responses. In this study, an integrative approach employing in silico analysis and wet-lab experiment was conducted to estimate the degrees of innate immune system relevant gene expression, neurotoxic Aβ42 generation and neuronal apoptosis in normal Drosophila melanogaster and a transgenic model of AD. Results demonstrated mRNA levels of antimicrobial peptide (AMP) genes gradually increased with age in wild-type flies, while which exhibited a trend for an initial decrease followed by subsequent increase during aging in the AD group. Time series and correlation analysis illustrated indicated a potential relationship between variation in AMP expression and Aβ42 concentration. In conclusion, our study provides evidence for abnormal gene expression of AMPs in AD flies with age, which is distinct from the expression profiles in the normal aging process. Aberrant AMP expression may participate in the onset and development of AD by inducing or accelerating Aβ deposition. These findings suggest that AMPs may serve as potential diagnostic biomarkers and therapeutic targets. However, further studies are required to elucidate the pathological effects and underlying mechanisms of AMP dysregulation in AD progression.

Background: Periodontitis is a chronic immuno-inflammatory disease characterized by inflammatory destruction of tooth-supporting tissues. Its pathogenesis involves a dysregulated local host immune response that is ineffective in combating microbial challenges. An integrated investigation of genes involved in mediating immune response suppression in periodontitis, based on multiple studies, can reveal genes pivotal to periodontitis pathogenesis. Here, we aimed to apply a deep learning (DL)-based autoencoder (AE) for predicting immunosuppression genes involved in periodontitis by integrating multiples omics datasets.Methods: Two periodontitis-related GEO transcriptomic datasets (GSE16134 and GSE10334) and immunosuppression genes identified from DisGeNET and HisgAtlas were included. Immunosuppression genes related to periodontitis in GSE16134 were used as input to build an AE, to identify the top disease-representative immunosuppression gene features. Using K-means clustering and ANOVA, immune subtype labels were assigned to disease samples and a support vector machine (SVM) classifier was constructed. This classifier was applied to a validation set (Immunosuppression genes related to periodontitis in GSE10334) for predicting sample labels, evaluating the accuracy of the AE. In addition, differentially expressed genes (DEGs), signaling pathways, and transcription factors (TFs) involved in immunosuppression and periodontitis were determined with an array of bioinformatics analysis. Shared DEGs common to DEGs differentiating periodontitis from controls and those differentiating the immune subtypes were considered as the key immunosuppression genes in periodontitis.Results: We produced representative molecular features and identified two immune subtypes in periodontitis using an AE. Two subtypes were also predicted in the validation set with the SVM classifier. Three “master” immunosuppression genes, PECAM1, FCGR3A, and FOS were identified as candidates pivotal to immunosuppressive mechanisms in periodontitis. Six transcription factors, NFKB1, FOS, JUN, HIF1A, STAT5B, and STAT4, were identified as central to the TFs-DEGs interaction network. The two immune subtypes were distinct in terms of their regulating pathways.Conclusion: This study applied a DL-based AE for the first time to identify immune subtypes of periodontitis and pivotal immunosuppression genes that discriminated periodontitis from the healthy. Key signaling pathways and TF-target DEGs that putatively mediate immune suppression in periodontitis were identified. PECAM1, FCGR3A, and FOS emerged as high-value biomarkers and candidate therapeutic targets for periodontitis.