Comprehensive Analysis of Prognostic and Genetic Signatures for General Transcription Factor III (GTF3) in Clinical Colorectal Cancer Patients Using Bioinformatics Approaches

Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Despite advances in diagnosis and treatment, including surgery, chemotherapy, and immunotherapy, accurate clinical markers are still lacking. The development of prognostic and predictive indicators, particularly in the context of personalized medicine, could significantly improve CRC patient management.

METHOD

In this retrospective study, we used FFPE blocks of tissue samples from CRC patients at Augusta University (AU) to quantify a custom 15-gene panel. To differentiate the tumor and adjacent normal regions (NAT), H&E staining was utilized. For the quantification of transcripts, we used the NanoString nCounter platform. Kaplan-Meier and Log-rank tests were used to perform survival analyses. Several independent datasets were explored to validate the gene signature. Orthogonal analyses included single-cell profiling, differential gene expression, immune cell deconvolution, neoantigen prediction, and biological pathway assessment.

RESULTS

A 3-gene signature (GTF3A, PKM, and VEGFA) was found to be associated with overall survival in the AU cohort (HR = 2.26, 95% CI 1.05-4.84, p = 0.02, 93 patients), TCGA cohort (HR = 1.57, 95% CI 1.05-2.35, p < 0.02, 435 patients) and four other GEO datasets. Independent single-cell analysis identified relatively higher expression of the 3-gene signature in the tumor region. Differential analysis revealed dysregulated tissue inflammation, immune dysfunction, and neoantigen load of cell cycle processes among high-risk patients compared to low-risk patients.

CONCLUSION

We developed a 3-gene signature with the potential for prognostic and predictive clinical assessment of CRC patients. This gene-based stratification offers a cost-effective approach to personalized cancer management. Further research using similar methods could identify therapy-specific gene signatures to strengthen the development of personalized medicine for CRC patients.

Unraveling Axonal Transcriptional Landscapes: Insights from iPSC-Derived Cortical Neurons and Implications for Motor Neuron Degeneration

Neuronal function and pathology are deeply influenced by the distinct molecular profiles of the axon and soma. Traditional studies have often overlooked these differences due to the technical challenges of compartment specific analysis. In this study, we employ a robust RNA-sequencing (RNA-seq) approach, using microfluidic devices, to generate high-quality axonal transcriptomes from iPSC-derived cortical neurons (CNs). We achieve high specificity of axonal fractions, ensuring sample purity without contamination. Comparative analysis revealed a unique and specific transcriptional landscape in axonal compartments, characterized by diverse transcript types, including protein-coding mRNAs, RNAs encoding ribosomal proteins (RPs), mitochondrial-encoded RNAs, and long non-coding RNAs (lncRNAs). Previous works have reported the existence of transcription factors (TFs) in the axon. Here, we detect a set of TFs specific to the axon and indicative of their active participation in transcriptional regulation. To investigate transcripts and pathways essential for central motor neuron (MN) degeneration and maintenance we analyzed KIF1C-knockout (KO) CNs, modeling hereditary spastic paraplegia (HSP), a disorder associated with prominent length-dependent degeneration of central MN axons. We found that several key factors crucial for survival and health were absent in KIF1C-KO axons, highlighting a possible role of these also in other neurodegenerative diseases. Taken together, this study underscores the utility of microfluidic devices in studying compartment-specific transcriptomics in human neuronal models and reveals complex molecular dynamics of axonal biology. The impact of KIF1C on the axonal transcriptome not only deepens our understanding of MN diseases but also presents a promising avenue for exploration of compartment specific disease mechanisms.

Disruption of pulmonary microvascular endothelial barrier by dysregulated claudin-8 and claudin-4: uncovered mechanisms in porcine reproductive and respiratory syndrome virus infection

The pulmonary endothelium is a dynamic and metabolically active monolayer of endothelial cells. Dysfunction of the pulmonary endothelial barrier plays a crucial role in the acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), frequently observed in the context of viral pneumonia. Dysregulation of tight junction proteins can lead to the disruption of the endothelial barrier and subsequent leakage. Here, the highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) served as an ideal model for studying ALI and ARDS. The alveolar lavage fluid of pigs infected with HP-PRRSV, and the supernatant of HP-PRRSV infected pulmonary alveolar macrophages were respectively collected to treat the pulmonary microvascular endothelial cells (PMVECs) in Transwell culture system to explore the mechanism of pulmonary microvascular endothelial barrier leakage caused by viral infection. Cytokine screening, addition and blocking experiments revealed that proinflammatory cytokines IL-1β and TNF-α, secreted by HP-PRRSV-infected macrophages, disrupt the pulmonary microvascular endothelial barrier by downregulating claudin-8 and upregulating claudin-4 synergistically. Additionally, three transcription factors interleukin enhancer binding factor 2 (ILF2), general transcription factor III C subunit 2 (GTF3C2), and thyroid hormone receptor-associated protein 3 (THRAP3), were identified to accumulate in the nucleus of PMVECs, regulating the transcription of claudin-8 and claudin-4. Meanwhile, the upregulation of ssc-miR-185 was found to suppress claudin-8 expression via post-transcriptional inhibition. This study not only reveals the molecular mechanisms by which HP-PRRSV infection causes endothelial barrier leakage in acute lung injury, but also provides novel insights into the function and regulation of tight junctions in vascular homeostasis.

KRAS/PI3K axis driven GTF3C6 expression and promotes LUAD via FAK pathway

INTRODUCTION

Effective targeting drugs for KRAS mutation-mediated Lung Adenocarcinoma (LUAD) are currently are limited.

OBJECTIVES

Investigating and intervening in the downstream key target genes of KRAS is crucial for clinically managing KRAS mutant-driven LUAD. GTF3C6, a newly identified member of the general transcription factor III (GTF3) family, plays a role in the transcription of RNA polymerase III (pol III)-dependent genes. However, its involvement in cancer remains unexplored.

METHODS

This study examined the expression, roles, and potential molecular mechanisms of GTF3C6 in LUAD tissues, LSL-KrasG12D/+;LSL-p53-/- LUAD mouse models, and LUAD patients-derived organoid using Western blot, qRT-PCR, immunofluorescence, immunohistochemistry, and gene manipulation assays.

RESULTS

We present the first evidence that GTF3C6 is highly expressed in LUAD tissues, LSL-KrasG12D/+;LSL-p53-/- LUAD mouse models, and LUAD organoids, correlating with poor clinical prognosis. Furthermore, GTF3C6 was found to promote anchorage-independent proliferation, migration, and invasion of LUAD cells. Mechanistically, KRAS mutation drives GTF3C6 expression through the PI3K pathway, and GTF3C6 knockdown reverses the malignant phenotype of KRAS mutation-driven LUAD cells. Additionally, the FAK pathway emerged as a crucial downstream signaling pathway through which GTF3C6 mediates the malignant phenotype of LUAD. Finally, GTF3C6 knockdown suppresses LUAD organoid formation and inhibits tumor growth in vivo.

CONCLUSION

Our findings demonstrate that GTF3C6, driven by KRAS mutation, promotes LUAD development by regulating FAK phosphorylation, suggesting its potential as a biomarker and therapeutic target in KRAS mutant-driven LUAD.

Integrated co-expression analysis of regulatory elements (miRNA, lncRNA, and TFs) in bovine monocytes induced by Str. uberis

Non-coding RNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), together with transcription factors, are critical pre-, co-, and post-transcriptional regulators. In addition to their criteria as ideal biomarkers, they have great potential in disease prognosis, diagnosis, and treatment of complex diseases. Investigation of regulatory mechanisms in the context of bovine mastitis, as most common and economic disease in the dairy industry, to identify elements influencing the expression of candidate genes as key regulators of the mammary immune response is not yet fully understood. Transcriptome profiles (50 RNA-Seq and 50 miRNA-Seq samples) of bovine monocytes induced by Str. uberis were used for co-expression module detection and preservation analysis using the weighted gene co-expression network analysis (WGCNA) approach. Assigned mi-, lnc-, and m-modules used to construct the integrated regulatory networks and miRNA-lncRNA-mRNA regulatory sub-networks. Remarkably, we have identified 18 miRNAs, five lncRNAs, and seven TFs as key regulators of str. uberis-induced mastitis. Most of the genes introduced here, mainly involved in immune response, inflammation, and apoptosis, were new to mastitis. These findings may help to further elucidate the underlying mechanisms of bovine mastitis, and the discovered genes may serve as signatures for early diagnosis and treatment of the disease.

Whole Exome Sequencing of Thymoma Patients Exhibiting Exceptional Responses to Pemetrexed Monotherapy

BACKGROUND

Pemetrexed is used for the chemotherapy of advanced thymoma. Exceptional responses of thymoma to pemetrexed treatment are not frequently observed. The underlying genetic mechanism of the exceptional responses remains unclear. We used whole-exome sequencing to explore the specific genomic aberrations that lead to an extreme and durable response.

METHODS

Whole-exome sequencing using NovaSeq6000 (150 bp paired-end sequencing) was performed on nine formalin-fixed paraffin-embedded tissues from patients with advanced thymomas treated with pemetrexed (two exceptional responders and seven typical responders).

RESULTS

We identified 284 somatic single-nucleotide variants (SNVs; 272 missense, 8 missense/splice-site, 3 stop-gain, and 1 stop-gain/splice-site), 34 insertions and deletions (Indels; 33 frameshift and one splice region), and 21 copy number variations (CNVs; 15 gains and six losses). No difference in the number of SNVs variants and distribution of deleterious Indels was observed between the exceptional and typical responders. Interestingly, arm-level chromosomal CNVs (15 gains and six losses) were detected in four patients, including an exceptional responder. The highest number of arm-level CNVs was observed in an exceptional responder.

CONCLUSION

Exceptional responders to pemetrexed for metastatic thymomas may be characterized by arm-level CNVs. Further, whole-genome and RNA sequencing studies should be performed.

PSMD8 can serve as potential biomarker and therapeutic target of the PSMD family in ovarian cancer: based on bioinformatics analysis and in vitro validation

BACKGROUND

The ubiquity-proteasome system is an indispensable mechanism for regulating intracellular protein degradation, thereby affecting human antigen processing, signal transduction, and cell cycle regulation. We used bioinformatics database to predict the expression and related roles of all members of the PSMD family in ovarian cancer. Our findings may provide a theoretical basis for early diagnosis, prognostic assessment, and targeted therapy of ovarian cancer.

METHODS

GEPIA, cBioPortal, and Kaplan-Meier Plotter databases were used to analyze the mRNA expression levels, gene variation, and prognostic value of PSMD family members in ovarian cancer. PSMD8 was identified as the member with the best prognostic value. The TISIDB database was used to analyze the correlation between PSMD8 and immunity, and the role of PSMD8 in ovarian cancer tissue was verified by immunohistochemical experiments. The relationship of PSMD8 expression with clinicopathological parameters and survival outcomes of ovarian cancer patients was analyzed. The effects of PSMD8 on malignant biological behaviors of invasion, migration, and proliferation of ovarian cancer cells were studied by in vitro experiments.

RESULTS

The expression levels of PSMD8/14 mRNA in ovarian cancer tissues were significantly higher than those in normal ovarian tissues, and the expression levels of PSMD2/3/4/5/8/11/12/14 mRNA were associated with prognosis. Up-regulation of PSMD4/8/14 mRNA expression was associated with poor OS, and the up-regulation of PSMD2/3/5/8 mRNA expression was associated with poor PFS in patients with ovarian serous carcinomas. Gene function and enrichment analysis showed that PSMD8 is mainly involved in biological processes such as energy metabolism, DNA replication, and protein synthesis. Immunohistochemical experiments showed that PSMD8 was mainly expressed in the cytoplasm and the expression level was correlated with FIGO stage. Patients with high PSMD8 expression had poor prognosis. Overexpression of PSMD8 significantly enhanced the proliferation, migration, and invasion abilities in ovarian cancer cells.

CONCLUSION

We observed different degrees of abnormal expression of members of PSMD family in ovarian cancer. Among these, PSMD8 was significantly overexpressed in ovarian malignant tissue, and was associated with poor prognosis. PSMDs, especially PSMD8, can serve as potential diagnostic and prognostic biomarkers and therapeutic targets in ovarian cancer.

SENP3 promotes tumor progression and is a novel prognostic biomarker in triple-negative breast cancer

Background

The clinical outcome of triple-negative breast cancer (TNBC) is poor. Finding more targets for the treatment of TNBC is an urgent need. SENPs are SUMO-specific proteins that play an important role in SUMO modification. Among several tumor types, SENPs have been identified as relevant biomarkers for progression and prognosis. The role of SENPs in TNBC is not yet clear.

Methods

The expression and prognosis of SENPs in TNBC were analyzed by TCGA and GEO data. SENP3 coexpression regulatory networks were determined by weighted gene coexpression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and Cox univariate analyses were used to develop a risk signature based on genes associated with SENP3. A time-dependent receiver operating characteristic (ROC) analysis was employed to evaluate a risk signature's predictive accuracy and sensitivity. Moreover, a nomogram was constructed to facilitate clinical application.

Results

The prognostic and expression effects of SENP family genes were validated using the TCGA and GEO databases. SENP3 was found to be the only gene in the SENP family that was highly expressed and associated with an unfavorable prognosis in TNBC patients. Cell functional experiments showed that knockdown of SENP3 leads to growth, invasion, and migration inhibition of TNBC cells in vitro. By using WGCNA, 273 SENP3-related genes were identified. Finally, 11 SENP3-related genes were obtained from Cox univariate analysis and LASSO regression. Based on this, a prognostic risk prediction model was established. The risk signature of SENP3-related genes was verified as an independent prognostic marker for TNBC patients.

Conclusion

Among SENP family genes, we found that SENP3 was overexpressed in TNBC and associated with a worse prognosis. SENP3 knockdown can inhibit tumor proliferation, invasion, and migration. In TNBC patients, a risk signature based on the expression of 11 SENP3-related genes may improve prognosis prediction. The established risk markers may be promising prognostic biomarkers that can guide the individualized treatment of TNBC patients.

N-Heterocycle based Degraders (PROTACs) Manifesting Anticancer Efficacy: Recent Advances

Proteolysis Targeting Chimeras (PROTACs) technology has emerged as a promising strategy for the treatment of undruggable therapeutic targets. Researchers have invested a great effort in developing druggable PROTACs; however, the problems associated with PROTACs, including poor solubility, metabolic stability, cell permeability, and pharmacokinetic profile, restrict their clinical utility. Thus, there is a pressing need to expand the size of the armory of PROTACs which will escalate the chances of pinpointing new PROTACs with optimum pharmacokinetic and pharmacodynamics properties. N- heterocycle is a class of organic frameworks that have been widely explored to construct new and novel PROTACs. This review provides an overview of recent efforts of medicinal chemists to develop N-heterocycle-based PROTACs as effective cancer therapeutics. Specifically, the recent endeavors centred on the discovery of PROTACs have been delved into various classes based on the E3 ligase they target (MDM2, IAP, CRBN, and other E3 ligases). Mechanistic insights revealed during the biological assessment of recently furnished Nheterocyclic- based PROTACs constructed via the utilization of ligands for various E3 ligases have been discussed.

The expression changes of transcription factors including ANKZF1, LEF1, CASZ1, and ATOH1 as a predictor of survival rate in colorectal cancer: a large-scale analysis

INTRODUCTION

Transcription factors (TFs) are essential for many biological processes and regulate the expression of several genes. This study's objective was to analyze the abnormalities in TF expression, their impact on patient prognosis, and related pathways in colorectal cancer (CRC).

METHOD

The expression alterations of all TFs were investigated using the cancer genome atlas and GSE39582 data. Clinical data were also used to study the association between TFs expression and patient prognosis through the Cox regression test, and a predictive model of CRC patient survival was constructed based on TFs expression. Co-expression network was used to discover TF-related pathways. To validate the findings, the RT-qPCR method was applied to CRC samples and adjacent normal tissue.

RESULTS

The findings revealed that ANKZF1, SALL4, SNAI1, TIGD1, LEF1, FOXS1, SIX4, and ETV5 expression levels increased in both cohorts and were linked to the poor prognosis. NR3C2, KLF4, CASZ1, FOXD2, ATOH1, SALL1, and RORC expression, on the other hand, exhibited a significant decrease, and their increase was related to the good prognosis of patients. The patient mortality risk model based on expression of mentioned TFs revealed that, independent of clinical characteristics, the expression of ANKZF1, LEF1, CASZ1, and ATOH1 could accurately predict patient survival rates. According to the co-expression network, increased transcription factors were linked to metastatic pathways, while decreasing TFs were involved to apoptotic pathways. RT-qPCR findings showed that FOXS1 expression was markedly overexpressed in CRC samples. However, in CRC samples, the expression of CASZ1 decreased.

CONCLUSION

In CRC, TFs expression of ANKZF1, LEF1, CASZ1 and ATOH1 are deregulated, which are associated with prognosis in patients. According to our findings, changes in the expression of the mentioned TFs have the potential to be considered diagnostic and prognostic biomarkers for CRC patients.

Polyadenylate-binding protein cytoplasmic 1 mediates alternative splicing events of immune-related genes in gastric cancer cells

Polyadenylate-binding protein cytoplasmic 1 (PABPC1) is dysregulated in malignancies, which is considered as a potential therapeutic target for many cancer types. By alternative splicing (AS) for gastric cancer (GC), we described PABPC1-modulated AS events in this study. PABPC1 expression was analyzed in 408 GC tissues from The Cancer Genome Altas (TCGA) database. Human gastric adenocarcinoma (AGS) cells were transfected with PABPC1-specific small interfering RNA (siPABPC1) with siCtrl as a negative control. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was done for the determination of transcripts. To detect the differentially expressed genes (DEGs) and 10 different types of AS events, RNA sequencing (RNA-seq) was performed. DEGs were analyzed for functional categories including gene ontology, and the Kyoto encyclopedia of genes and genomes pathway were analyzed for DEGs. GC displayed an elevated expression of PABPC1. PABPC1 was efficiently knocked down in AGS cells. Here, we excavated 1234 PABPC1-regulated DEGs, among which 502 were down-regulated and 732 were up-regulated compared to the siCtrl group. A total of 94 DEGs were involved in inflammation and immune response. Results from qRT-PCR validated the up-regulation of 10 immune and inflammation-related DEGs in the siPABPC1 group. PABPC1 deficiency causes 1304 AS events differentially occurred in AGS cells. The most common type of AS events regulated by PABPC2 is alternative 5' splice sites. qRT-PCR confirmed the transcription level of five immune-related genes, in which AS events were detected in the siPABPC1 group. PABPC1 knockdown mediates AS events and thus the transcript level of immune and inflammation-related genes in AGS cells. PABPC1-regulated oncogenic AS events display potential as targets for therapeutic development.

8-Hydroxydaidzein Downregulates JAK/STAT, MMP, Oxidative Phosphorylation, and PI3K/AKT Pathways in K562 Cells

A metabolite isolated from fermented soybean, 8-hydroxydaidzein (8-OHD, 7,8,4′-trihydroxyisoflavone, NSC-678112), is widely used in ethnopharmacological research due to its anti-proliferative and anti-inflammatory effects. We reported previously that 8-OHD provoked reactive oxygen species (ROS) overproduction, and induced autophagy, apoptosis, breakpoint cluster region-Abelson murine leukemia viral oncogene (BCR-ABL) degradation, and differentiation in K562 human chronic myeloid leukemia (CML) cells. However, how 8-OHD regulates metabolism, the extracellular matrix during invasion and metastasis, and survival signaling pathways in CML remains largely unexplored. High-throughput technologies have been widely used to discover the therapeutic targets and pathways of drugs. Bioinformatics analysis of 8-OHD-downregulated differentially expressed genes (DEGs) revealed that Janus kinase/signal transducer and activator of transcription (JAK/STAT), matrix metalloproteinases (MMPs), c-Myc, phosphoinositide 3-kinase (PI3K)/AKT, and oxidative phosphorylation (OXPHOS) metabolic pathways were significantly altered by 8-OHD treatment. Western blot analyses validated that 8-OHD significantly downregulated cytosolic JAK2 and the expression and phosphorylation of STAT3 dose- and time-dependently in K562 cells. Zymography and transwell assays also confirmed that K562-secreted MMP9 and invasion activities were dose-dependently inhibited by 8-OHD after 24 h of treatment. RT-qPCR analyses verified that 8-OHD repressed metastasis and OXPHOS-related genes. In combination with DisGeNET, it was found that 8-OHD’s downregulation of PI3K/AKT is crucial for controlling CML development. A STRING protein–protein interaction analysis further revealed that AKT and MYC are hub proteins for cancer progression. Western blotting revealed that AKT phosphorylation and nuclear MYC expression were significantly inhibited by 8-OHD. Collectively, this systematic investigation revealed that 8-OHD exerts anti-CML effects by downregulating JAK/STAT, PI3K/AKT, MMP, and OXPHOS pathways, and MYC expression. These results could shed new light on the development of 8-OHD for CML therapy.

Novel Insights into the Prognosis and Immunological Value of the SLC35A (Solute Carrier 35A) Family Genes in Human Breast Cancer

According to statistics 2020, female breast cancer (BRCA) became the most commonly diagnosed malignancy worldwide. Prognosis of BRCA patients is still poor, especially in population with advanced or metastatic. Particular functions of each members of the solute carrier 35A (SLC35A) gene family in human BRCA are still unknown regardless of awareness that they play critical roles in tumorigenesis and progression. Using integrated bioinformatics analyses to identify therapeutic targets for specific cancers based on transcriptomics, proteomics, and high-throughput sequencing, we obtained new information and a better understanding of potential underlying molecular mechanisms. Leveraging BRCA dataset that belongs to The Cancer Genome Atlas (TCGA), which were employed to clarify SLC35A gene expression levels. Then we used a bioinformatics approach to investigate biological processes connected to SLC35A family genes in BRCA development. Beside that, the Kaplan-Meier estimator was leveraged to explore predictive values of SLC35A family genes in BCRA patients. Among individuals of this family gene, expression levels of SLC35A2 were substantially related to poor prognostic values, result from a hazard ratio of 1.3 (with 95 percent confidence interval (95% CI: 1.18-1.44), the p for trend (ptrend) is 3.1 × 10-7). Furthermore, a functional enrichment analysis showed that SLC35A2 was correlated with hypoxia-inducible factor 1A (HIF1A), heat shock protein (HSP), E2 transcription factor (E2F), DNA damage, and cell cycle-related signaling. Infiltration levels observed in specific types of immune cell, especially the cluster of differentiation found on macrophages and neutrophils, were positively linked with SLC35A2 expression in multiple BRCA subclasses (luminal A, luminal B, basal, and human epidermal growth factor receptor 2). Collectively, SLC35A2 expression was associated with a lower recurrence-free survival rate, suggesting that it could be used as a biomarker in treating BRCA.

Prognostic and immune infiltration signatures of proteasome 26S subunit, non-ATPase (PSMD) family genes in breast cancer patients

The complexity of breast cancer includes many interacting biological processes that make it difficult to find appropriate therapeutic treatments. Therefore, identifying potential diagnostic and prognostic biomarkers is urgently needed. Previous studies demonstrated that 26S proteasome delta subunit, non-ATPase (PSMD) family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcriptional expressions of PSMD family genes in breast cancer still remain largely unexplored. Consequently, we used a holistic bioinformatics approach to explore PSMD genes involved in breast cancer patients by integrating several high-throughput databases, including The Cancer Genome Atlas (TCGA), cBioPortal, Oncomine, and Kaplan-Meier plotter. These data demonstrated that PSMD1, PSMD2, PSMD3, PSMD7, PSMD10, PSMD12, and PSMD14 were expressed at significantly higher levels in breast cancer tissue compared to normal tissues. Notably, the increased expressions of PSMD family genes were correlated with poor prognoses of breast cancer patients, which suggests their roles in tumorigenesis. Meanwhile, network and pathway analyses also indicated that PSMD family genes were positively correlated with ubiquinone metabolism, immune system, and cell-cycle regulatory pathways. Collectively, this study revealed that PSMD family members are potential prognostic biomarkers for breast cancer progression and possible promising clinical therapeutic targets.

Potential Prognostic Biomarkers of OSBPL Family Genes in Patients with Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy with poor survival outcomes. In addition, oxysterol-binding protein-like (OSBPL) family members are reported to be involved in lipid binding and transport and play critical roles in tumorigenesis. However, relationships between PDAC and OSBPL family members have not comprehensively been elucidated. In this study, we used the Oncomine and GEPIA 2 databases to analyze OSBPL transcription expressions in PDAC. The Kaplan–Meier plotter and TIMER 2.0 were used to assess the relationships between overall survival (OS) and immune-infiltration with OSBPL family members. Co-expression data from cBioPortal were downloaded to assess the correlated pathways with OSBPL gene family members using DAVID. The expressions of OSBPL3, OSBPL8, OSBPL10, and OSBPL11 were found to be highly upregulated in PDAC. Low expressions of OSBPL3, OSBPL8, and OSBPL10 indicated longer OS. The functions of OSBPL family members were mainly associated with several potential signaling pathways in cancer cells, including ATP binding, integrin binding, receptor binding, and the renin-angiotensin system (RAS) signaling pathway. The transcription levels of OSBPL gene family members were connected with several immune infiltrates. Collectively, OSBPL family members are influential biomarkers for the early diagnosis of PDAC and have prognostic value, with the promise of precise treatment of PDAC in the future.

Potential Therapeutic and Prognostic Values of LSM Family Genes in Breast Cancer

In recent decades, breast cancer (BRCA) has become one of the most common diseases worldwide. Understanding crucial genes and their signaling pathways remain an enormous challenge in evaluating the prognosis and possible therapeutics. The "Like-Smith" (LSM) family is known as protein-coding genes, and its member play pivotal roles in the progression of several malignancies, although their roles in BRCA are less clear. To discover biological processes associated with LSM family genes in BRCA development, high-throughput techniques were applied to clarify expression levels of LSMs in The Cancer Genome Atlas (TCGA)-BRCA dataset, which was integrated with the cBioPortal database. Furthermore, we investigated prognostic values of LSM family genes in BCRA patients using the Kaplan-Meier database. Among genes of this family, LSM4 expression levels were highly associated with poor prognostic outcomes with a hazard ratio of 1.35 (95% confidence interval 1.21-1.51, p for trend = 3.4 × 10-7). MetaCore and GlueGo analyses were also conducted to examine transcript expression signatures of LSM family members and their coexpressed genes, together with their associated signaling pathways, such as "Cell cycle role of APC in cell cycle regulation" and "Immune response IL-15 signaling via MAPK and PI3K cascade" in BRCA. Results showed that LSM family members, specifically LSM4, were significantly correlated with oncogenesis in BRCA patients. In summary, our results suggested that LSM4 could be a prospective prognosticator of BRCA.

Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.

Prognoses and genomic analyses of proteasome 26S subunit, ATPase (PSMC) family genes in clinical breast cancer

Breast cancer is a complex disease, and several processes are involved in its development. Therefore, potential therapeutic targets need to be discovered for these patients. Proteasome 26S subunit, ATPase gene (PSMC) family members are well reported to be involved in protein degradation. However, their roles in breast cancer are still unknown and need to be comprehensively researched. Leveraging publicly available databases, such as cBioPortal and Oncomine, for high-throughput transcriptomic profiling to provide evidence-based targets for breast cancer is a rapid and robust approach. By integrating the aforementioned databases with the Kaplan–Meier plotter database, we investigated potential roles of six PSMC family members in breast cancer at the messenger RNA level and their correlations with patient survival. The present findings showed significantly higher expression profiles of PSMC2, PSMC3, PSMC4, PSMC5, and PSMC6 in breast cancer compared to normal breast tissues. Besides, positive correlations were also revealed between PSMC family genes and ubiquinone metabolism, cell cycle, and cytoskeletal remodeling. Meanwhile, we discovered that high levels of PSMC1, PSMC3, PSMC4, PSMC5, and PSMC6 transcripts were positively correlated with poor survival, which likely shows their importance in breast cancer development. Collectively, PSMC family members have the potential to be novel and essential prognostic biomarkers for breast cancer development.

Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach

Breast cancer is a heterogeneous disease involving complex interactions of biological processes; thus, it is important to develop therapeutic biomarkers for treatment. Members of the dipeptidyl peptidase (DPP) family are metalloproteases that specifically cleave dipeptides. This family comprises seven members, including DPP3, DPP4, DPP6, DPP7, DPP8, DPP9, and DPP10; however, information on the involvement of DPPs in breast cancer is lacking in the literature. As such, we aimed to study their roles in this cancerous disease using publicly available databases such as cBioportal, Oncomine, and Kaplan–Meier Plotter. These databases comprise comprehensive high-throughput transcriptomic profiles of breast cancer across multiple datasets. Furthermore, together with investigating the messenger RNA expression levels of these genes, we also aimed to correlate these expression levels with breast cancer patient survival. The results showed that DPP3 and DPP9 had significantly high expression profiles in breast cancer tissues relative to normal breast tissues. High expression levels of DPP3 and DPP4 were associated with poor survival of breast cancer patients, whereas high expression levels of DPP6, DPP7, DPP8, and DPP9 were associated with good prognoses. Additionally, positive correlations were also revealed of DPP family genes with the cell cycle, transforming growth factor (TGF)-beta, kappa-type opioid receptor, and immune response signaling, such as interleukin (IL)-4, IL6, IL-17, tumor necrosis factor (TNF), and interferon (IFN)-alpha/beta. Collectively, DPP family members, especially DPP3, may serve as essential prognostic biomarkers in breast cancer.