Pan-cancer analysis of non-oncogene addiction to DNA repair

Reuniting philosophy and science to advance cancer research

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

The biological significance of cuproptosis-key gene MTF1 in pan-cancer and its inhibitory effects on ROS-mediated cell death of liver hepatocellular carcinoma

Metal regulatory transcription factor 1 (MTF1) has been reported to be correlated with several human diseases, especially like cancers. Exploring the underlying mechanisms and biological functions of MTF1 could provide novel strategies for clinical diagnosis and therapy of cancers. In this study, we conducted the comprehensive analysis to evaluate the profiles of MTF1 in pan-cancer. For example, TIMER2.0, TNMplot and GEPIA2.0 were employed to analyze the expression values of MTF1 in pan-cancer. The methylation levels of MTF1 were evaluated via UALCAN and DiseaseMeth version 2.0 databases. The mutation profiles of MTF1 in pan-cancers were analyzed using cBioPortal. GEPIA2.0, Kaplan-Meier plotter and cBioPortal were also used to explore the roles of MTF1 in cancer prognosis. We found that high MTF1 expression was related to poor prognosis of liver hepatocellular carcinoma (LIHC) and brain lower grade glioma (LGG). Also, high expression level of MTF1 was associated with good prognosis of kidney renal clear cell carcinoma (KIRC), lung cancer, ovarian cancer and breast cancer. We investigated the genetic alteration and methylation levels of MTF1 between the primary tumor and normal tissues. The relationship between MTF1 expression and several immune cells was analyzed, including T cell CD8 + and dendritic cells (DC). Mechanically, MTF1-interacted molecules might participate in the regulation of metabolism-related pathways, such as peptidyl-serine phosphorylation, negative regulation of cellular amide metabolic process and peptidyl-threonine phosphorylation. Single cell sequencing indicated that MTF1 was associated with angiogenesis, DNA repair and cell invasion. In addition, in vitro experiment indicated knockdown of MTF1 resulted in the suppressed cell proliferation, increased reactive oxygen species (ROS) and promoted cell death in LIHC cells HepG2 and Huh7. Taken together, this pan-cancer analysis of MTF1 has implicated that MTF1 could play an essential role in the progression of various human cancers.

Pan-Cancer Analysis on the Oncogenic Role of Programmed Cell Death 10

Purpose

Programmed cell death factor 10 (PDCD10) is associated with intercellular junction, cytoskeleton organization, cell proliferation, apoptosis, exocytosis, and angiogenesis. However, the role of PDCD10 in human cancer is unclear. This study aims to explore the role of PDCD10 in various tumors and its possible mechanism through bioinformatics analysis.

Methods

We verified the expression of the PDCD10 gene based on data from the ONCOMINE, TIMER2.0, and TISDB databases. The correlation of PDCD10 with prognosis of patients with different tumors was analyzed using data from the GEPIA2 database. Proteins bound to PDCD10 were analyzed from the STRING database. PDCD10, PDCD10-binding proteins, and associated candidate genes were analyzed in DAVID for functional and pathway analyses. We also evaluated the immunological, clinical, and genetic aspects of distinct cancers by using TIMER2.0 and the connection between PDCD10 expression and tumor immune subtypes by using TISDB. Single-cell sequencing data from the CancerSEA database were used to characterize cancer cell functional states and generate heat maps.

Results

PDCD10 overexpression is linked to certain molecular subtypes of human cancer. Low PDCD10 expression in patients with bladder urothelial carcinoma (BLCA), lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), adrenocortical carcinoma (ACC), head and neck squamous cell carcinoma (HNSC), kidney chromophobe carcinoma (KICH), brain lower grade glioma (LGG), pancreatic adenocarcinoma (PAAD), uterine corpus endometrial carcinoma (UCEC), oral squamous cell carcinoma (OSCC), and esophageal adenocarcinoma (ESAD) was correlated with favorable OS, whereas high PDCD10 expression in patients with LUSC, KIRC, READ, SKCM, and THYM was correlated with good prognosis. STRING network prediction results showed that 20 proteins, namely, paxillin (PXN), CCM2 scaffold protein (CCM2), TRAF3 interacting protein 3 (TRAF3IP3), FGFR1 oncogene partner 2 (FGFR1OP2), chromosome 4 open reading frame 19 (C4orf19), suppressor of IKBKE 1 (SIKE1), serine/threonine kinase 25 (STK25), striatin (STRN), protein phosphatase 2 catalytic subunit alpha (PPP2CA), mammalian sterile-20-like kinase 4 (MST4), MOB family member 4 (MOB4), protein phosphatase 2 scaffold subunit Abeta (PPP2R1B), sarcolemma-associated protein (SLMAP), serine/threonine kinase 24 (STK24), striatin 4 (STRN4), STRN3, protein phosphatase 2 scaffold subunit A alpha (PPP2R1A), striatin interacting protein 1 (STRIP1), CTTNBP2 N-terminal like (CTTNBP2NL), and cortactin binding protein 2 (CTTNBP2), can bind to PDCD10. Gene enrichment analysis suggested that PDCD10 is involved in the occurrence of different tumors through the Hippo signalling pathway, RNA transport, mRNA monitoring pathway, endocytosis, and T cell receptor signalling pathway. An inverse relationship was found between PDCD10 expression and cancer-associated fibroblasts in LUSC and TGCT, and PDCD10 expression was strongly connected with immunological subtypes, such as C1 (wound healing), C2 (interferon-gamma dominant), C3 (inflammation), C4 (lymphocyte depletion), C5 (immune silenced), and C6 (TGF-beta dominant). Finally, analysis of single-cell sequencing data revealed that PDCD10 expression is linked to epigenetic reprogramming, DNA repair, cell cycle progression, cell differentiation, inflammation, cell proliferation, cell differentiation, cell invasion, and angiogenesis.

Conclusion

The results of our investigation demonstrate that PDCD10 has an oncogenic function in many cancer types. This study provides a reference for future research on antitumor therapeutic targets.

Exonucleases: Degrading DNA to Deal with Genome Damage, Cell Death, Inflammation and Cancer

Although DNA degradation might seem an unwanted event, it is essential in many cellular processes that are key to maintaining genomic stability and cell and organism homeostasis. The capacity to cut out nucleotides one at a time from the end of a DNA chain is present in enzymes called exonucleases. Exonuclease activity might come from enzymes with multiple other functions or specialized enzymes only dedicated to this function. Exonucleases are involved in central pathways of cell biology such as DNA replication, repair, and death, as well as tuning the immune response. Of note, malfunctioning of these enzymes is associated with immune disorders and cancer. In this review, we will dissect the impact of DNA degradation on the DNA damage response and its links with inflammation and cancer.

EF-Hand Domain-Containing Protein D2 (EFHD2) Correlates with Immune Infiltration and Predicts the Prognosis of Patients: A Pan-Cancer Analysis

Background

EF-hand domain-containing protein D2 (EFHD2) has recently been reported to participate in initiation of cancer. More evidence indicates that EFHD2 plays an important role in tumors, but the pan-cancer analysis of EFHD2 is still very limited.

Methods

In this study, we downloaded the original mRNA expression data and SNP data of 33 kinds of tumor data. The gene expression data of different tissues were downloaded from the GTEX database, combined with TCGA data and corrected to calculate the difference of gene expression. The data of total survival time (OS) and progression-free survival (PFS) of TCGA patients were downloaded from the Xena database to further survey the relationship between the EFHD2 expression and prognosis. The CIBERSORT algorithm was used to analyze the RNA-seq data of 33 kinds of cancer patients in different subgroups. In this study, NCI-60 drug sensitivity data and RNA-seq data were downloaded to explore the relationship between genes and common antineoplastic drug sensitivity through correlation analysis. In this study, GSEA analysis was carried out from the Molecular Signature database through the packages of "clusterprofiler" and "enrichplot." By comparing the differences of signal pathways between high and low gene expression groups, the possible molecular mechanism of prognostic differences among 33 kinds of tumors was determined.

Results

Our results indicated that EFHD2 was highly expressed in 23 kinds of tumors. In addition, EFHD2 was associated with stage in many kinds of tumors. The expression of EFHD2 was closely related to the OS of 12 kinds of cancer patients. In addition, Kaplan-Meier- (KM-) plot survival analysis indicated that the high expression of EFHD2 was related to the poor OS of 5 kinds of cancer, and the expression of EFHD2 was closely related to the PFI of 5 kinds of cancer patients. The expression of EFHD2 was closely related to immune infiltration, among which 18 cancers were significantly correlated with CD8T cells, 14 cancers were significantly correlated with T regulatory (Tregs) cells, 15 cancers were significantly correlated with CD4 memory activated Tcells, and EFHD2 was significantly correlated with common tumor-related regulatory genes such as TGF beta signaling, TNFA signaling, hypoxia, scorch death, DNA repair, autophagy, and iron death-related genes. The expression level of EFHD2 was significantly correlated with each tumor of TMB, including STAD, SARC, ACC, THYM, KICH, THCA, and TGCT. In MSI, there were significant differences in THYM, STAD, THCA, and TGCT. We used the CellMiner database to explore the sensitivity between EFHD2 gene and common antineoplastic drugs and found that the prediction of high expression of EFHD2 was related to the resistance of many antineoplastic drugs. In renal cell carcinoma, the high expression of EFHD2 is mainly concentrated in ALLOGRAFT_REJECTION, REACTIVE_OXYGEN_SPECIES_PATHWAY, INTERFERON_GAMMA_RESPONSE, IL6_JAK_STAT3_SIGNALING, INTERFERON_ALPHA_RESPONSE, and other signal pathways. GO results showed that the genes were mainly enriched in response to interferon-gamma, antigen processing and presentation, cellular response to interferon-gamma, and other pathways. KEGG results demonstrated that EFHD2 was mainly rich in phagosome, Epstein-Barr virus infection, Staphylococcus aureus infection, and other pathways. The results of Kaplan-Meier survival analysis demonstrated that the high expression of EFHD2 was significantly related to the poor prognosis.

Conclusion

Our findings highlight the predictive value of EFHD2 in cancer and provide a potential research direction for elucidating the role of EFHD2 in tumorigenesis and drug resistance.