In Silico Integration of Transcriptome and Interactome Predicts an ETP-ALL-Specific Transcriptional Footprint that Decodes its Developmental Propensity

Background Peripheral T-cell lymphoma (PTCL) is a subtype of non-Hodgkin's lymphoma that occurs primarily at extranodal sites and is commonly treated using chemotherapy and radiotherapy. PTCL is more malignant than other lymphoid tumors, resulting in a poor prognosis.The 5-year recurrence rate remains high, and there is a lack of standard treatment for patients with relapse-resistant disease. However, the molecular mechanisms underlying the resistance of peripheral T-cell lymphoma cells to chemotherapeutic drugs, as well as identifying strategies to overcome drug resistance remains unclear. In this study, we aimed to identify pivotal genes and signaling pathways associated with chemotherapy resistance in PTCL. Methods In this study, a total of 5 healthy controls and 7 clinical patients were enrolled; 4 patients were classified as chemotherapy sensitive, and 3 patients were classified as chemotherapy resistant. Peripheral blood samples were collected from each participant, and total RNA was extracted from the white blood cells. RNA sequencing was conducted on the Illumina HiSeq platform to obtain comprehensive gene expression profiles. Subsequently, the expression patterns of the DEGs associated with the most enriched signaling pathways, with a special focus on cancer-related genes, were validated using quantitative real-time polymerase chain reaction (qRT–PCR) in peripheral TCL patients. Results RNA sequencing (RNA-seq) analysis revealed 4063 differentially expressed genes (DEGs) in peripheral T-cell lymphoma specimens from patients with chemotherapy resistance, of which 1128 were upregulated and 2935 were downregulated. Subsequent quantitative gene expression analysis confirmed a differential expression pattern in all the libraries, with 9 downregulated genes and 10 upregulated genes validated through quantitative real-time PCR in 6 clinical specimens from patients with chemotherapy resistance. KEGG pathway analysis revealed significant alterations in several pathways, with 6 downregulated pathways and 9 upregulated pathways enriched in the DEGs. Notably, the TNF signaling pathway, which is extensively regulated, was among the pathways that exhibited significant changes. These findings suggest that DEGs and the TNF signaling pathway may play crucial roles in chemotherapy resistance in peripheral T-cell lymphoma. Conclusion Our study revealed that the expression of specific genes, including TNFRSF1B, TRADD2, and MAP3K7, may play an important role in chemotherapy resistance in peripheral T-cell lymphoma. Moreover, we identified the downregulation of the TNF signaling pathway, a crucial pathway involved in cell survival, death, and differentiation, as a potential contributor to the development of chemotherapy resistance in peripheral T-cell lymphoma. These findings provide valuable insights into the molecular mechanisms underlying chemotherapy resistance and highlight potential targets for overcoming treatment resistance in this challenging disease.

Section: Discussionmentioning

confidence: 99%

The RNA sequencing results revealed the expression of different genes and signaling pathways during chemotherapy resistance in peripheral T-cell lymphoma

Lan,

Tao,

et al. 2024

“…Further longitudinal data on ctDNA concentrations or methylation status variations concerning disease progression or treatment response should be undertaken. On the other hand, there is a recommendation to conduct more investigations on dimension reduction approaches [23], which are critical to enhancing cancer research. This method can facilitate the selection of the most informative potential biomarkers that could impact the diagnostic precision.…”

Section: Discussionmentioning

confidence: 99%

Circulating-tumour DNA methylation of HAND1 gene: a promising biomarker in early detection of colorectal cancer

Shavali,

Moradi,

Tahmaseb

et al. 2024

Background Colorectal cancer (CRC) is one of the significant global health concerns with an increase in cases. Regular screening tests are crucial for early detection as it is often asymptomatic in the initial stages. Liquid biopsies, a non-invasive approach that examines biomarkers in biofluids, offer a promising future in diagnosing and screening cancer. Circulating-tumour DNA (ctDNA) is the genetic material in biofluids released into the circulatory system by cells. ctDNA is a promising marker for monitoring patients since cancer cells display distinct DNA methylation patterns compared to normal cells. The potential of our research to contribute to early detection and improved patient outcomes is significant. Aims The primary objective of this research project was to explore the HAND1 methylation levels in plasma ctDNA as a potential biomarker for diagnosing CRC and evaluate the methylation level of the well-established gene SPET9 to compare it with the methylation level of HAND1. Materials and methods Plasma samples were collected from 30 CRC patients and 15 healthy individuals, with CRC samples obtained pre-treatment. ctDNA was extracted and treated with bisulfite for methylation status assessment. Quantitative methylation-specific PCR (qMS-PCR) was performed for HAND1 and SEPT9, using β-actin (ACTB gene) as a reference. The study aims to evaluate the potential of these genes as diagnostic biomarkers for CRC, contributing to early detection and improved patient outcomes. Results Our study yielded significant results: 90% of CRC patients (27 out of 30) had hypermethylation in the SEPT9 gene, and 83% (25 out of 30) exhibited hypermethylation in the HAND1 gene. The methylation levels of both genes were significantly higher in CRC patients than in healthy donors. These findings underscore the potential of SEPT9 and HAND1 methylation as promising biomarkers for diagnosing CRC, potentially leading to early detection and improved patient outcomes. Conclusion These findings highlight the potential of SEPT9 and HAND1 methylation as promising biomarkers for diagnosing CRC. However, further research and validation studies are needed to confirm these findings and to explore their clinical utility in CRC diagnosis and management.

“…It is still necessary to discover the underlying genomic defects and mysterious mechanisms in individuals for treatment response [29]. By using an intertomics-based approach, transcriptome-based subcluster identification can be achieved directly at the clinical level, which may be critical for predicting potential drug targets for individual subclusters [5]. Therefore, RNA-seq can be implemented in the diagnostic workflow of ALL and enhances the individual molecular diagnostic risk classification of ALL [4,30].…”

Section: Discussionmentioning

confidence: 99%

“…Beyond cytogenetics and fluorescence in situ hybridization, gene expression profiling has revealed new cytogenetic subgroups that display specific gene expression patterns. RNA-seq is believed to be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of leukemia [4][5][6][7]. Gene expression patternbased therapy could be a potential upcoming strategy.…”

Section: Introductionmentioning

confidence: 99%

The potential role of RNA sequencing in diagnosing unexplained insensitivity to conventional chemotherapy in pediatric patients with B-cell acute lymphoblastic leukemia

Li,

Huang,

Zhu

et al. 2024

Pediatric B-cell acute lymphoblastic leukemia (B-ALL) is a highly heterogeneous disease. According to large-scale RNA sequencing (RNA-seq) data, B-ALL patients can be divided into more than 10 subgroups. However, many genomic defects associated with resistance mechanisms have not yet been identified. As an individual clinical tool for molecular diagnostic risk classification, RNA-seq and gene expression pattern-based therapy could be potential upcoming strategies. In this study, we retrospectively analyzed the RNA-seq gene expression profiles of 45 children whose molecular diagnostic classifications were inconsistent with the response to chemotherapy. The relationship between the transcriptome and chemotherapy response was analyzed. Fusion gene identification was conducted for the included patients who did not have known high-risk associated fusion genes or gene mutations. The most frequently detected fusion gene pair in the high-risk group was the DHRSX duplication, which is a novel finding. Fusions involving ABL1, LMNB2, NFATC1, PAX5, and TTYH3 at onset were more frequently detected in the high-risk group, while fusions involving LFNG, TTYH3, and NFATC1 were frequently detected in the relapse group. According to the pathways involved, the underlying drug resistance mechanism is related to DNA methylation, autophagy, and protein metabolism. Overall, the implementation of an RNA-seq diagnostic system will identify activated markers associated with chemotherapy response, and guide future treatment adjustments.