CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics

Pan-cancer prognosis, immune infiltration, and drug resistance characterization of lung squamous cell carcinoma tumor microenvironment-related genes

Background

The tumor microenvironment (TME) plays an important role in cancer development; however, its implications in lung squamous cell carcinoma (LUSC) and pan-cancer have been poorly understood.

Methods

In this study, The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression Data (ESTIMATE) datasets were applied to identify differentially expressed genes. Additionally, online public databases were utilized for in-depth bioinformatics analysis of pan-cancer datasets to investigate the prognostic implications of TME-related genes further.

Results

Our study demonstrated a significant association between stromal scores, immune scores, and specific clinical characteristics in LUSC patients. C3AR1, CSF1R, CCL2, CCR1, and CD14 were identified as prognostic genes related to the TME. All TME-related prognostic genes demonstrated varying degrees of correlation with immune infiltration subtypes and tumor cell stemness. Moreover, our study revealed that TME-related prognostic genes, particularly C3AR1 and CCR1, might contribute to drug resistance in cancer cells.

Conclusions

The identified TME-related prognostic genes, particularly C3AR1 and CCR1, have potential implications for understanding and targeting drug resistance mechanisms in cancer cells.

Targeting neddylation and sumoylation in chemoresistant triple negative breast cancer

Triple negative breast cancer (TNBC) accounts for 15-20% of breast cancer cases in the United States. Systemic neoadjuvant chemotherapy (NACT), with or without immunotherapy, is the current standard of care for patients with early-stage TNBC. However, up to 70% of TNBC patients have significant residual disease once NACT is completed, which is associated with a high risk of developing recurrence within two to three years of surgical resection. To identify targetable vulnerabilities in chemoresistant TNBC, we generated longitudinal patient-derived xenograft (PDX) models from TNBC tumors before and after patients received NACT. We then compiled transcriptomes and drug response profiles for all models. Transcriptomic analysis identified the enrichment of aberrant protein homeostasis pathways in models from post-NACT tumors relative to pre-NACT tumors. This observation correlated with increased sensitivity in vitro to inhibitors targeting the proteasome, heat shock proteins, and neddylation pathways. Pevonedistat, a drug annotated as a NEDD8-activating enzyme (NAE) inhibitor, was prioritized for validation in vivo and demonstrated efficacy as a single agent in multiple PDX models of TNBC. Pharmacotranscriptomic analysis identified a pathway-level correlation between pevonedistat activity and post-translational modification (PTM) machinery, particularly involving neddylation and sumoylation targets. Elevated levels of both NEDD8 and SUMO1 were observed in models exhibiting a favorable response to pevonedistat compared to those with a less favorable response in vivo. Moreover, a correlation emerged between the expression of neddylation-regulated pathways and tumor response to pevonedistat, indicating that targeting these PTM pathways may prove effective in combating chemoresistant TNBC.

A bioinformatics approach to systematically analyze the molecular patterns of monkeypox virus-host cell interactions

Monkeypox has been spreading worldwide since May 2022, when the World Health Organization (WHO) declared the outbreak a "public health emergency of international concern." The spread of monkeypox has posed a serious threat to the health of people around the world, but few studies have been conducted, and the molecular mechanism of monkeypox after infection remains unclear. We therefore implemented a transcriptome analysis to identify signaling pathways and biomarkers in monkeypox-infected cells to help understand monkeypox-host cell interactions. In this study, datasets GSE36854 and GSE11234 were obtained from GEO. Of these, 84 significantly different genes were identified in the dataset GSE36854, followed by KEGG, GO analysis protein-protein interaction (PPI) construction, and Hub gene extraction. We also analyzed the expression regulation of hub genes and screened for drugs targeting hub genes. The results showed that monkeypox-infected cells significantly activated the cellular immune response. The top 10 hub genes are IER3, IFIT2, IL11, ZC3H12A, EREG, IER2, NFKBIE, FST, IFIT1 and AREG. AP-26113 and itraconazole can be used to counteract the inhibitory effect of monkeypox on IFIT1 and IFIT2 and serve as candidate drugs for the treatment of monkeypox virus infection. IRF1 may also be a transcription factor of IFIT. Our results provide a new entry point for understanding how monkeypox virus interacts with its host.

CLLU1 as an emerging biomarker in chronic lymphoid leukemia

CLLU1, a disease-specific gene associated with chronic lymphoid leukemia (CLL), is located on chromosome 12q22. Previous studies considered CLLU1 to be a non-coding RNA; however, recent research has discovered that its coding sequence region possesses the potential to encode a short peptide similar to interleukin-4. Remarkably, abnormally elevated expression of CLLU1 has only been detected in chronic lymphoid leukemia among all hematological cancers. High CLLU1 expression often indicates more malignant pathological features and an unfavorable prognosis for patients. Importantly, the expression level of CLLU1 remains unaffected by the passage of time or therapeutic interventions, thus rendering it a novel prognostic marker. This article provides a comprehensive summary of relevant research findings on CLLU1 in the context of CLL prognosis and clinical applications, aiming to guide subsequent theoretical and clinical investigations in this field.

Machine learning-based identification of a consensus immune-derived gene signature to improve head and neck squamous cell carcinoma therapy and outcome

Background

Head and neck squamous cell carcinoma (HNSCC), an extremely aggressive tumor, is often associated with poor outcomes. The standard anatomy-based tumor-node-metastasis staging system does not satisfy the requirements for screening treatment-sensitive patients. Thus, an ideal biomarker leading to precise screening and treatment of HNSCC is urgently needed.

Methods

Ten machine learning algorithms-Lasso, Ridge, stepwise Cox, CoxBoost, elastic network (Enet), partial least squares regression for Cox (plsRcox), random survival forest (RSF), generalized boosted regression modelling (GBM), supervised principal components (SuperPC), and survival support vector machine (survival-SVM)-as well as 85 algorithm combinations were applied to construct and identify a consensus immune-derived gene signature (CIDGS).

Results

Based on the expression profiles of three cohorts comprising 719 patients with HNSCC, we identified 236 consensus prognostic genes, which were then filtered into a CIDGS, using the 10 machine learning algorithms and 85 algorithm combinations. The results of a study involving a training cohort, two testing cohorts, and a meta-cohort consistently demonstrated that CIDGS was capable of accurately predicting prognoses for HNSCC. Incorporation of several core clinical features and 51 previously reported signatures, enhanced the predictive capacity of the CIDGS to a level which was markedly superior to that of other signatures. Notably, patients with low CIDGS displayed fewer genomic alterations and higher immune cell infiltrate levels, as well as increased sensitivity to immunotherapy and other therapeutic agents, in addition to receiving better prognoses. The survival times of HNSCC patients with high CIDGS, in particular, were shorter. Moreover, CIDGS enabled accurate stratification of the response to immunotherapy and prognoses for bladder cancer. Niclosamide and ruxolitinib showed potential as therapeutic agents in HNSCC patients with high CIDGS.

Conclusion

CIDGS may be used for stratifying risks as well as for predicting the outcome of patients with HNSCC in a clinical setting.

CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity

Drug therapy is vital in cancer treatment. Accurate analysis of drug sensitivity for specific cancers can guide healthcare professionals in prescribing drugs, leading to improved patient survival and quality of life. However, there is a lack of web-based tools that offer comprehensive visualization and analysis of pancancer drug sensitivity. We gathered cancer drug sensitivity data from publicly available databases (GEO, TCGA and GDSC) and developed a web tool called Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) using Shiny. CPADS currently includes transcriptomic data from over 29 000 samples, encompassing 44 types of cancer, 288 drugs and more than 9000 gene perturbations. It allows easy execution of various analyses related to cancer drug sensitivity. With its large sample size and diverse drug range, CPADS offers a range of analysis methods, such as differential gene expression, gene correlation, pathway analysis, drug analysis and gene perturbation analysis. Additionally, it provides several visualization approaches. CPADS significantly aids physicians and researchers in exploring primary and secondary drug resistance at both gene and pathway levels. The integration of drug resistance and gene perturbation data also presents novel perspectives for identifying pivotal genes influencing drug resistance. Access CPADS at https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.

Integrative analysis revealed a correlation of PIAS family genes expression with prognosis, immunomodulation and chemotherapy

BACKGROUND

Protein inhibitor of activated STATs (PIAS) has pleiotropic biological effects, such as protein post-translational modification, transcriptional coregulation and gene editing. It is reported that PIAS family genes are also correlated with immune cells infiltration in cancers that highlights their unnoticed biological role in tumor progression. However, the relationship of their expression with prognosis, immune cell infiltration, tumor microenvironment, and immunotherapy in pan-cancer has been rarely reported.

METHODS

The multi-omics data were used to investigate the expression level of PIAS family members in pan-cancer, and the prognostic value of their expression in different tumors was analyzed by univariate Cox regression and Kaplan-Meier. Correlation analysis was used to investigate the relationship of PIAS gene expression with tumor microenvironment, immune infiltrating subtypes, stemness score and drug sensitivity. In addition, we also used wound healing and transwell assays to verify the biological effects of PIAS family gene expression on invasion and metastasis of HCC cells.

RESULTS

We found that PIAS family genes expression is significantly heterogeneous in tumors by multi-genomic analysis, and associated with poor prognosis in patients with multiple types of cancer. Furthermore, we also found that genetic alterations of PIAS family genes were not only common in different types of human tumors, but were also significantly associated with disease-free survival (DFS) across pan-cancer. Single-cell analysis revealed that PIAS family genes were mainly distributed in monocytes/macrophages. Additionally, we also found that their expression was associated with tumor microenvironment (including stromal cells and immune cells) and stemness score (DNAss and RNAss). Drug sensitivity analysis showed that PIAS family genes were able to predict the response to chemotherapy and immunotherapy. PIAS family genes expression is closely related to tumor metastasis, especially PIAS3. High PIAS3 expression significantly promotes the migration and invasion of liver cancer cell lines (HCC-LM3 and MHCC97-H).

CONCLUSIONS

Taking together, these findings contribute to determine whether the PIAS family genes are a potential oncogenic target gene, which have important contribution for the development of cancer immunotherapy.

Activity of the Ubiquitin-activating Enzyme Inhibitor TAK-243 in Adrenocortical Carcinoma Cell Lines, Patient-derived Organoids, and Murine Xenografts

Current treatment options for metastatic adrenocortical carcinoma (ACC) have limited efficacy, despite the common use of mitotane and cytotoxic agents. This study aimed to identify novel therapeutic options for ACC. An extensive drug screen was conducted to identify compounds with potential activity against ACC cell lines. We further investigated the mechanism of action of the identified compound, TAK-243, its synergistic effects with current ACC therapeutics, and its efficacy in ACC models including patient-derived organoids and mouse xenografts. TAK-243, a clinical ubiquitin-activating enzyme (UAE) inhibitor, showed potent activity in ACC cell lines. TAK-243 inhibited protein ubiquitination in ACC cells, leading to the accumulation of free ubiquitin, activation of the unfolded protein response, and induction of apoptosis. TAK-243 was found to be effluxed out of cells by MDR1, a drug efflux pump, and did not require Schlafen 11 (SLFN11) expression for its activity. Combination of TAK-243 with current ACC therapies (e.g., mitotane, etoposide, cisplatin) produced synergistic or additive effects. In addition, TAK-243 was highly synergistic with BCL2 inhibitors (Navitoclax and Venetoclax) in preclinical ACC models including patient-derived organoids. The tumor suppressive effects of TAK-243 and its synergistic effects with Venetoclax were further confirmed in a mouse xenograft model. These findings provide preclinical evidence to support the initiation of a clinical trial of TAK-243 in patients with advanced-stage ACC. TAK-243 is a promising potential treatment option for ACC, either as monotherapy or in combination with existing therapies or BCL2 inhibitors.

SIGNIFICANCE

ACC is a rare endocrine cancer with poor prognosis and limited therapeutic options. We report that TAK-243 is active alone and in combination with currently used therapies and with BCL2 and mTOR inhibitors in ACC preclinical models. Our results suggest implementation of TAK-243 in clinical trials for patients with advanced and metastatic ACC.

A pyrimidine metabolism-related signature for prognostic and immunotherapeutic response prediction in hepatocellular carcinoma by integrating analyses

BACKGROUND

Hepatocellular carcinoma (HCC), with discouraging morbidity and mortality, ranks as one of the most prevalent tumors worldwide. Pyrimidine metabolism is a critical process that regulates DNA and RNA synthesis in cells. It is imperative to investigate the significance of pyrimidine metabolism in liver cancer.

METHODS

Transcriptome and clinical data were downloaded from the TCGA database and the GEO database. The genes related to pyrimidine metabolism were sourced from the MSigDB. The pyrimidine metabolism-related signature (PMRS) was constructed through Cox regression and Lasso regression and then verified in the external validation set from the ICGC database. Functional enrichment, immune infiltration analysis, drug sensitivity, and Immunophenoscore (IPS) were further implemented to predict the response to immunotherapy. The role of PMRS in the malignant phenotype of hepatocellular carcinoma was explored by conducting a series of in vitro experiments.

RESULTS

Our study developed a four-genes PMRS which demonstrates a substantial correlation with the prognosis of HCC patients, serving as an independent predictor in clinical practice. The result of risk-stratified analysis yielded evidence that low-risk patients experienced more favorable clinical outcomes. The nomogram exhibited remarkable prognostic predictive value. The subsequent results revealed that low-risk patients manifested a more promising response to immunotherapy. Moreover, the results of cell experiments demonstrated that the downregulation of DCK markedly inhibited the malignant phenotype of hepatocellular carcinoma.

CONCLUSIONS

Our pyrimidine metabolism-centered prognostic signature accurately predicts overall survival, immune status, and treatment response in hepatocellular carcinoma (HCC) patients, offering innovative insights for precise diagnosis, personalized treatment, and improved prognosis.

Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma

Two APOBEC (apolipoprotein-B mRNA editing enzyme catalytic polypeptide-like) DNA cytosine deaminase enzymes (APOBEC3A and APOBEC3B) generate somatic mutations in cancer, driving tumour development and drug resistance. Here we used single cell RNA sequencing to study APOBEC3A and APOBEC3B expression in healthy and malignant mucosal epithelia, validating key observations with immunohistochemistry, spatial transcriptomics and functional experiments. Whereas APOBEC3B is expressed in keratinocytes entering mitosis, we show that APOBEC3A expression is confined largely to terminally differentiating cells and requires Grainyhead-like transcription factor 3 (GRHL3). Thus, in normal tissue, neither deaminase appears to be expressed at high levels during DNA replication, the cell cycle stage associated with APOBEC-mediated mutagenesis. In contrast, we show that in squamous cell carcinoma tissues, there is expansion of GRHL3 expression and activity to a subset of cells undergoing DNA replication and concomitant extension of APOBEC3A expression to proliferating cells. These findings indicate a mechanism for acquisition of APOBEC3A mutagenic activity in tumours.

Exploring the role of ubiquitin regulatory X domain family proteins in cancers: bioinformatics insights, mechanisms, and implications for therapy

UBXD family (UBXDF), a group of proteins containing ubiquitin regulatory X (UBX) domains, play a crucial role in the imbalance of proliferation and apoptotic in cancer. In this study, we summarised bioinformatics proof on multi-omics databases and literature on UBXDF's effects on cancer. Bioinformatics analysis revealed that Fas-associated factor 1 (FAF1) has the largest number of gene alterations in the UBXD family and has been linked to survival and cancer progression in many cancers. UBXDF may affect tumour microenvironment (TME) and drugtherapy and should be investigated in the future. We also summarised the experimental evidence of the mechanism of UBXDF in cancer, both in vitro and in vivo, as well as its application in clinical and targeted drugs. We compared bioinformatics and literature to provide a multi-omics insight into UBXDF in cancers, review proof and mechanism of UBXDF effects on cancers, and prospect future research directions in-depth. We hope that this paper will be helpful for direct cancer-related UBXDF studies.

Systematic pan-cancer analyses of the potential function of the Golgi scaffold protein PAQR3

Progesterone and AdipoQ Receptor 3 (PAQR3) is a member of the AdipoQ receptor. Our previous studies have found that PAQR3 plays a role as a candidate inhibitor in cardiac adenocarcinoma, breast cancer, gastric cancer and colorectal cancer, but the systematic analysis of PAQR3 in tumors is currently lacking. The objective of this study was to investigate the prognostic and therapeutic value of PAQR3 in 31 tumors. Through the analysis of TCGA, UALCAN, GEO, GEPIA2, TIMER, Kaplan-Meier plotter, TISIDB and other databases, it was found that the expression level of PAQR3 changed significantly in different tumor types, and the expression level of Neuroblastoma was very high. And the level of Prostate adenocarcinoma is low. In addition, the expression level of PAQR3 in Cholangiocarcinoma, Esophageal carcinoma, Head and neck squamous carcinoma, Liver Hepatocellular Carcinoma, Lung Adenocarcinoma and Lung squamous cell carcinoma was significantly higher than that in normal tissues. However, the expression level of PAQR3 in Breast Cancer, Kidney Renal Clear Cell Carcinoma, Kidney renal papillary cell carcinoma, Prostate Adenocarcinoma, Rectum Adenocarcinoma, Thyroid Cancer and Uterine Corpus Endometrial Carcinoma was lower than that in normal tissues. Subsequently, we explored the value of PAQR3 as a prognostic indicator of cancer. In Acute Myeloid Leukemia, Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Kidney Chromophobe, and Thyroid Cancer, PAQR3 expression was positively correlated with OS and DSS, while in Rectum Adenocarcinoma, PAQR3 expression was negatively correlated with OS. PAQR3 high expression group Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Uveal Melanoma, Kidney Chromophobe and DFI were positively correlated. PAQR3 can be used as a risk factor for the prognosis of multiple tumors. Then, we discussed the correlation between PAQR3 and immunology, and found that PAQR3 has a wide range of mutations in various tumor types, the most common mutation type is missense mutation, and common mutation types also include amplification, depth deletion, splicing, truncation and structural variation. Among the tumor samples with PAQR3 alterations, mutation occurred in all tumor samples except prostate adenocarcinoma and adrenal cortical carcinoma, head and neck squamous cell carcinoma, brain low-grade glioma, and kidney clear cell carcinoma, while esophageal adenocarcinoma had the highest total alteration frequency. PAQR3 was strongly associated with CNV in 18 tumors, particularly in Ovarian cancer, Lung squamous cell carcinoma, and Adenoid cystic carcinoma. On the other hand, PAQR3 has a higher SNV frequency in Uterine Corpus Endometrial Carcinoma, Skin Cutaneous Melanoma and Lung Adenocarcinoma, among which Uterine Corpus Endometrial Carcinoma has the highest SNV frequency. These results showed that PAQR3 expression levels were significantly correlated with tumor mutation load, microsatellite instability, neoantigens, and purity. In summary, PAQR3 can affect the tumor microenvironment and has potential for chemotherapy. Finally, we investigated the role of PAQR3 in tumor resistance and found that the expression of PAQR3 affects the efficacy of multiple chemotherapy drugs. Based on these studies, we found that PAQR3 plays an important role in cancer and has potential in tumor diagnosis and prognosis.

Pan-cancer and single-cell analysis reveal THRAP3 as a prognostic and immunological biomarker for multiple cancer types

Background: Thyroid hormone receptor-associated protein 3 (THRAP3) is of great significance in DNA damage response, pre-mRNA processing, and nuclear export. However, the biological activities of THRAP3 in pan-cancer remain unexplored. We aimed to conduct a comprehensive analysis of THRAP3 and validate its expression levels in lung cancer. Methods: A pan-cancer analysis was conducted to study the correlation of THRAP3 expression with clinical outcome and the tumor microenvironment based on the available bioinformatics databases. The protein levels of THRAP3 were explored in lung cancer by immunohistochemistry (IHC) analysis. Single-cell sequencing (ScRNA-seq) analysis was employed to investigate the proportions of each cell type in lung adenocarcinoma (LUAD) and adjacent normal tissues, along with the expression levels of THRAP3 within each cell type. Results: THRAP3 is upregulated in multiple cancer types but exhibits low expression in lung squamous cell carcinoma (LUSC). immunohistochemistry results showed that THRAP3 is a lowly expression in LUAD and LUSC. THRAP3 elevation had a poor prognosis in kidney renal clear cell carcinoma and a prolonged survival time in kidney chromophobe, brain lower-grade glioma and skin cutaneous melanoma, as indicated by the KM curve. Single-cell analysis confirmed that the proportions of T/B cells, macrophages, and fibroblasts were significantly elevated in LUAD tissues, and THRAP3 is specifically overexpressed in mast cells. Conclusion: Our findings uncover that THRAP3 is a promising prognostic biomarker and immunotherapeutic target in multiple cancers, but in LUAD and LUSC, it may be a protective gene.

Identification of breast cancer subgroups and immune characterization based on glutamine metabolism-related genes

Immunotherapy is a promising treatment for breast cancer (BC). However, due to individual differences and tumor heterogeneity, immunotherapy is only applicable to some BC patients. Glutamine metabolism plays a role in inhibiting immunotherapy, but its role in BC is limitedly studied. Therefore, we aimed to identify different BC subgroups based on glutamine metabolism and characterize the features of different subgroups to provide guidance for personalized immunotherapy for BC patients. Using unsupervised clustering analysis, we classified BC patients in The Cancer Genome Atlas (TCGA) with glutamine metabolism-related genes and obtained low-risk (LR) and high-risk (HR) subgroups. Survival analysis revealed that prognosis of LR subgroup was notably better than HR subgroup. Through ssGSEA and CIBERSORT methods, we disclosed that infiltration levels of B cells, Mast cells, T helper cells, and Th2 cells, and Type II IFN Response immune function were notably higher in LR subgroup than in HR subgroup. The Wilcox algorithm comparison denoted that DEPTH of LR subgroup was significantly lower than HR subgroup. The TIDE of LR subgroup was significantly higher than HR subgroup. Functional annotation of differentially expressed genes revealed that channel activity and the Estrogen signaling pathway may be related to BC prognosis. Ten hub genes were selected between the subgroups through the STRING database and Cytoscape, and their correlation with drugs was predicted on the CellMiner website. This study analyzed the immune characteristics of BC subgroups based on glutamine metabolism and provided reference for prognosis prediction and personalized immunotherapy.

Current advances in comprehensive omics data mining for oncology and cancer research

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

An emerging biomarker for the diagnosis and treatment of esophageal squamous cell carcinoma - Aurora A

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a prominent form of esophageal cancer. Aurora A (AURKA), an enzyme that phosphorylates serine and threonine, has a vital function in controlling the process of separating chromosomes during cell division. The contribution of this entity has been documented in the advancement of malignant proliferations, including tumors occurring in the breast, stomach, and ovaries.

METHODS

The potential molecular mechanism of AURKA is comprehensively examined through the analysis of bulk RNA-seq and single-cell RNA-seq data obtained from publicly available databases. This analysis encompasses various aspects such as expression levels, prognosis, and functional pathways, among others.

RESULTS

The upregulation of AURKA in ESCC has been found to be correlated with the overall survival of patients. The functional annotation and pathway enrichment analysis conducted in this study lead to the conclusion that AURKA participates in the regulation of a number of malignant processes connected to cell proliferation, such as cell cycle control, apoptosis, and the p53 signaling pathway. Additionally, AURKA has been found to be associated with drug sensitivity and has an impact on the infiltration of tumor-infiltrating immune cells in ESCC.

CONCLUSIONS

AURKA exhibits potential as a prognostic and therapeutic biomarker linked to the regulation of cell cycle and cell proliferation.

Triosephosphate isomerase 1 may be a risk predictor in laryngeal squamous cell carcinoma: a multi-centered study integrating bulk RNA, single-cell RNA, and protein immunohistochemistry

BACKGROUND

Although great progress has been made in anti-cancer therapy, the prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains unsatisfied. Quantities of studies demonstrate that glycolytic reprograming is essential for the progression of cancers, where triosephosphate isomerase 1 (TPI1) serves as a catalytic enzyme. However, the clinicopathological significance and potential biological functions of TPI1 underlying LSCC remains obscure.

METHODS

We collected in-house 82 LSCC tissue specimens and 56 non-tumor tissue specimens. Tissue microarrays (TMA) and immunohistochemical (IHC) experiments were performed. External LSCC microarrays and bulk RNA sequencing data were integrated to evaluate the expression of TPI1. We used a log-rank test and the CIBERSORT algorithm to assess the prognostic value of TPI1 and its association with the LSCC microenvironment. Malignant laryngeal epithelial cells and immune-stromal cells were identified using inferCNV and CellTypist. We conducted a comprehensive analysis to elucidate the molecular functions of TPI1 in LSCC tissue and single cells using Pearson correlation analysis, high dimensional weighted gene co-expression analysis, gene set enrichment analysis, and clustered regularly interspaced short palindromic repeats (CRISPR) screen. We explored intercellular communication patterns between LSCC single cells and immune-stromal cells and predicted several therapeutic agents targeting TPI1.

RESULTS

Based on the in-house TMA and IHC analysis, TPI1 protein was found to have a strong positive expression in the nucleus of LSCC cells but only weakly positive activity in the cytoplasm of normal laryngeal cells (p < 0.0001). Further confirmation of elevated TPI1 mRNA expression was obtained from external datasets, comparing 251 LSCC tissue samples to 136 non-LSCC tissue samples (standardized mean difference = 1.06). The upregulated TPI1 mRNA demonstrated a high discriminative ability between LSCC and non-LSCC tissue (area under the curve = 0.91; sensitivity = 0.87; specificity = 0.79), suggesting its potential as a predictive marker for poor prognosis (p = 0.037). Lower infiltration abundance was found for plasma cells, naïve B cells, monocytes, and neutrophils in TPI-high expression LSCC tissue. Glycolysis and cell cycle were significantly enriched pathways for both LSCC tissue and single cells, where heat shock protein family B member 1, TPI1, and enolase 1 occupied a central position. Four outgoing communication patterns and two incoming communication patterns were identified from the intercellular communication networks. TPI1 was predicted as an oncogene in LSCC, with CRISPR scores less than -1 across 71.43% of the LSCC cell lines. TPI1 was positively correlated with the half maximal inhibitory concentration of gemcitabine and cladribine.

CONCLUSIONS

TPI1 is dramatically overexpressed in LSCC than in normal tissue, and the high expression of TPI1 may promote LSCC deterioration through its metabolic and non-metabolic functions. This study contributes to advancing our knowledge of LSCC pathogenesis and may have implications for the development of targeted therapies in the future.

The crucial role of single-stranded DNA binding in enhancing sensitivity to DNA-damaging agents for Schlafen 11 and Schlafen 13

Schlafen (SLFN) 11 enhances cellular sensitivity to various DNA-damaging anticancer agents. Among the human SLFNs (SLFN5/11/12/13/14), SLFN11 is unique in its drug sensitivity and ability to block replication under DNA damage. In biochemical analysis, SLFN11 binds single-stranded DNA (ssDNA), and this binding is enhanced by the dephosphorylation of SLFN11. In this study, human cell-based assays demonstrated that a point mutation at the ssDNA-binding site of SLFN11 or a constitutive phosphorylation mutant abolished SLFN11-dependent drug sensitivity. Additionally, we discovered that nuclear SLFN13 with a point mutation mimicking the DNA-binding site of SLFN11 was recruited to chromatin, blocked replication, and enhanced drug sensitivity. Through generating multiple mutants and structure analyses of SLFN11 and SLFN13, we identified protein phosphatase 2A as a binding partner of SLFN11 and the putative binding motif in SLFN11. These findings provide crucial insights into the unique characteristics of SLFN11, contributing to a better understanding of its mechanisms.

Platelet-related gene risk score: a predictor for pancreatic cancer microenvironmental signature, chemosensitivity and prognosis

Recent studies have indicated that platelets may play a role in the advancement of pancreatic cancer by supporting tumor growth and increasing resistance to chemotherapy. This study aims to develop a prognostic model for pancreatic cancer using a platelet-related gene risk score. Prognostic platelet-related genes (PRGs) were identified from public databases and analyzed using cluster analysis. We investigated the microenvironment signatures and gene mutation patterns across different PRG-based molecular subtypes of pancreatic cancer. A prognostic model based on PRGs was developed using LASSO-Cox Regression Analysis. Additionally, we examined the correlation between the risk score and tumor clinical characteristics, as well as drug sensitivity. Two molecular subtypes, cluster C1 and C2, were identified. Cluster C2 was associated with a poorer prognosis compared to Cluster C1. The C1 group exhibited higher scores for activated CD8+ T cells, central memory CD4+ T cells, and natural killer T cells. The C2 group demonstrated a higher frequency of gene mutations. We established and validated a novel prognostic prediction model and platelet-related gene risk score for pancreatic cancer. The risk score was positively correlated with T stage, N stage, and tumor grade, and it presented a significant prognostic value compared to other clinical factors. In conclusion, a novel prognostic prediction model focusing on platelet involvement in pancreatic cancer has been developed, offering potential benefits for future drug therapies and clinical prognostic assessments.

Molecular data representation based on gene embeddings for cancer drug response prediction

Cancer drug response prediction is a crucial task in precision medicine, but existing models have limitations in effectively representing molecular profiles of cancer cells. Specifically, when these models represent molecular omics data such as gene expression, they employ a one-hot encoding-based approach, where a fixed gene set is selected for all samples and omics data values are assigned to specific positions in a vector. However, this approach restricts the utilization of embedding-vector-based methods, such as attention-based models, and limits the flexibility of gene selection. To address these issues, our study proposes gene embedding-based fully connected neural networks (GEN) that utilizes gene embedding vectors as input data for cancer drug response prediction. The GEN allows for the use of embedding-vector-based architectures and different gene sets for each sample, providing enhanced flexibility. To validate the efficacy of GEN, we conducted experiments on three cancer drug response datasets. Our results demonstrate that GEN outperforms other recently developed methods in cancer drug prediction tasks and offers improved gene representation capabilities. All source codes are available at https://github.com/DMCB-GIST/GEN/ .

Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment

Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.

A systemic analysis of monocarboxylate transporters in ovarian cancer and possible therapeutic interventions

Monocarboxylate transporters (MCTs) play an immense role in metabolically active solid tumors by regulating concentration-dependent transport of different important monocarboxylates including pyruvate and lactate and are encoded by the SLC16A family of genes. Given the vast array of functions, these transporters play in oncogenesis, our objective was to look into the association of MCT1 (SLC16A1), MCT2 (SLC16A7), MCT3 (SLC16A8), and MCT4 (SLC16A3) with Epithelial ovarian cancer (EOC) pathophysiology by exploiting various publicly available databases and web resources. Few of the in silico findings were confirmed via in vitro experiments in EOC cell lines, SKOV3 and OAW-42. MCT1 and MCT4 were found to be upregulated at the mRNA level in OC tissues compared to normal. However, only higher level of MCT4 mRNA was found to be associated with poor patient survival. MCT4 was positively correlated with gene families responsible for invasion, migration, and immune modification, proving it to be one of the most important MCTs for therapeutic intervention. We compared the effects of MCT1/2 blocker SR13800 and a broad-spectrum MCT blocker α-Cyano Hydroxy Cinnamic Acid (α-CHCA) and discovered that α-CHCA has a greater effect on diminishing the invasive behavior of the cancer cells than MCT1/2 blocker SR13800. From our study, MCT4 has emerged as a prospective marker for predicting poor patient outcomes and a potential therapeutic target.

PBK correlates with prognosis, immune escape and drug response in LUAD

PBK (PDZ-binding kinase) is a protein-coding gene that encodes a serine/threonine protein kinase associated with the dual-specific mitogen-activated protein kinase (MAPKK) family. Overexpression of this gene is closely linked to tumor development. In this study, we aimed to investigate the role of PBK in lung adenocarcinoma (LUAD) progression, prognosis, and immune evasion. We conducted a pan-cancer analysis of PBK to examine its expression and prognostic value. In the LUAD cohort, we analyzed PBK expression, prognosis, mutational features, and immune infiltration in groups with different PBK expression levels. We constructed a PBK-associated genomic model, integrated it into a nomogram, and compared high and low-risk subgroups. In our pan-cancer analysis, PBK was significantly upregulated, particularly in LUAD patients, and displayed poor prognosis. The high PBK expression group had many deletion mutations but still showed gene upregulation. Immune infiltration analysis indicated that PBK-triggered immune escape in the high expression group might relate to antigen presentation, dendritic cell, and CD8+ T cell infiltration. We constructed a 5-gene prognostic model and a nomogram to quantify individual survival probabilities. The PBK-associated gene prognostic model reliably predicted patient prognosis and drug response. Our findings offer new insights into PBK-induced immune escape and targeted therapy during LUAD development, providing valuable suggestions for clinical treatment approaches.

Diagnostic implications of lncRNA NORAD in breast cancer

This study aimed to assess the expression levels of non-coding RNA activated by DNA damage (NORAD) in the cells, tissues, and serum of breast cancer (BRCA) patients and benign breast nodules and investigate its association with clinicopathological characteristics and prognosis in BRCA. NORAD was analyzed using TCGA-BRCA, GSE77308, Cellminer, and Sangerbox databases, revealing its significance in BRCA prognosis, immune microenvironment, and cell function. Serum samples from 38 BRCA patients, 80 patients with benign breast nodules (50 fibroadenoma and 30 breast adenosis cases), and 42 healthy individuals were collected from Zhejiang Xiaoshan Hospital. NORAD expression was quantified using quantitative reverse transcription PCR (RT-qPCR). Differential NORAD expression between benign and malignant breast nodules and its relationship to clinicopathological characteristics were assessed. NORAD demonstrated elevated expression in BRCA patient serum compared to healthy individuals and those with benign breast nodules (P < 0.05). Moreover, its expression correlated with TNM-stage, lymph node metastasis, and luminal classification. These findings highlight the elevated NORAD expression in BRCA patient serum and its correlation with clinicopathological characteristics, providing insights into its potential as a diagnostic biomarker or therapeutic target.

Guanylate-binding protein 1 modulates proteasomal machinery in ovarian cancer

Guanylate-binding protein 1 (GBP1) is known as an interferon-γ-induced GTPase. Here, we used genetically modified ovarian cancer (OC) cells to study the role of GBP1. The data generated show that GBP1 inhibition constrains the clonogenic potential of cancer cells. In vivo studies revealed that GBP1 overexpression in tumors promotes tumor progression and reduces median survival, whereas GBP1 inhibition delayed tumor progression with longer median survival. We employed proteomics-based thermal stability assay (CETSA) on GBP1 knockdown and overexpressed OC cells to study its molecular functions. CETSA results show that GBP1 interacts with many members of the proteasome. Furthermore, GBP1 inhibition sensitizes OC cells to paclitaxel treatment via accumulated ubiquitinylated proteins where GBP1 inhibition decreases the overall proteasomal activity. In contrast, GBP1-overexpressing cells acquired paclitaxel resistance via boosted cellular proteasomal activity. Overall, these studies expand the role of GBP1 in the activation of proteasomal machinery to acquire chemoresistance.

MiR-181a targets STING to drive PARP inhibitor resistance in BRCA- mutated triple-negative breast cancer and ovarian cancer

BACKGROUND

Poly (ADP-ribose) polymerase inhibitors (PARPi) are approved for the treatment of BRCA-mutated breast cancer (BC), including triple-negative BC (TNBC) and ovarian cancer (OvCa). A key challenge is to identify the factors associated with PARPi resistance; although, previous studies suggest that platinum-based agents and PARPi share similar resistance mechanisms.

METHODS

Olaparib-resistant (OlaR) cell lines were analyzed using HTG EdgeSeq miRNA Whole Transcriptomic Analysis (WTA). Functional assays were performed in three BRCA-mutated TNBC cell lines. In-silico analysis were performed using multiple databases including The Cancer Genome Atlas, the Genotype-Tissue Expression, The Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, and Gene Omnibus Expression.

RESULTS

High miR-181a levels were identified in OlaR TNBC cell lines (p = 0.001) as well as in tumor tissues from TNBC patients (p = 0.001). We hypothesized that miR-181a downregulates the stimulator of interferon genes (STING) and the downstream proinflammatory cytokines to mediate PARPi resistance. BRCA1 mutated TNBC cell lines with miR-181a-overexpression were more resistant to olaparib and showed downregulation in STING and the downstream genes controlled by STING. Extracellular vesicles derived from PARPi-resistant TNBC cell lines horizontally transferred miR-181a to parental cells which conferred PARPi-resistance and targeted STING. In clinical settings, STING levels were positively correlated with interferon gamma (IFNG) response scores (p = 0.01). In addition, low IFNG response scores were associated with worse response to neoadjuvant treatment including PARPi for high-risk HER2 negative BC patients (p = 0.001). OlaR TNBC cell lines showed resistance to platinum-based drugs. OvCa cell lines resistant to platinum showed resistance to olaparib. Knockout of miR-181a significantly improved olaparib sensitivity in OvCa cell lines (p = 0.001).

CONCLUSION

miR-181a is a key factor controlling the STING pathway and driving PARPi and platinum-based drug resistance in TNBC and OvCa. The miR-181a-STING axis can be used as a potential marker for predicting PARPi responses in TNBC and OvCa tumors.

Pan-cancer analysis revealing that PTPN2 is an indicator of risk stratification for acute myeloid leukemia

The non-receptor protein tyrosine phosphatases gene family (PTPNs) is involved in the tumorigenesis and development of many cancers, but the role of PTPNs in acute myeloid leukemia (AML) remains unclear. After a comprehensive evaluation on the expression patterns and immunological effects of PTPNs using a pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas, the most valuable gene PTPN2 was discovered. Further investigation of the expression patterns of PTPN2 in different tissues and cells showed a robust correlation with AML. PTPN2 was then systematically correlated with immunological signatures in the AML tumor microenvironment and its differential expression was verified using clinical samples. In addition, a prediction model, being validated and compared with other models, was developed in our research. The systematic analysis of PTPN family reveals that the effect of PTPNs on cancer may be correlated to mediating cell cycle-related pathways. It was then found that PTPN2 was highly expressed in hematologic diseases and bone marrow tissues, and its differential expression in AML patients and normal humans was verified by clinical samples. Based on its correlation with immune infiltrates, immunomodulators, and immune checkpoint, PTPN2 was found to be a reliable biomarker in the immunotherapy cohort and a prognostic predictor of AML. And PTPN2'riskscore can accurately predict the prognosis and response of cancer immunotherapy. These findings revealed the correlation between PTPNs and immunophenotype, which may be related to cell cycle. PTPN2 was differentially expressed between clinical AML patients and normal people. It is a diagnostic biomarker and potentially therapeutic target, providing targeted guidance for clinical treatment.

Drug metabolism-related gene ABCA1 augments temozolomide chemoresistance and immune infiltration abundance of M2 macrophages in glioma

Gliomas are the most prevalent primary tumor in the central nervous system, with an abysmal 5-year survival rate and alarming mortality. The current standard management of glioma is maximum resection of tumors followed by postoperative chemotherapy with temozolomide (TMZ) or radiotherapy. Low chemosensitivity of TMZ in glioma treatment eventuates limited therapeutic efficacy or treatment failure. Hence, overcoming the resistance of glioma to TMZ is a pressing question. Our research centered on identifying the drug metabolism-related genes potentially involved in TMZ-treated resistance of glioma through several bioinformatics datasets and cell experiments. One efflux transporter, ATP-binding cassette transporter subfamily A1 (ABCA1), was discovered with an upregulated expression level and signaled poor clinical outcomes for glioma patients. The transcript level of ABCA1 significantly elevated across the TMZ-resistant glioma cells in contrast with non-resistant cells. Over-expressed ABCA1 restrained the drug activity of TMZ, and ABCA1 knockdown improved the treatment efficacy. Meanwhile, the results of molecular docking between ABCA1 protein and TMZ showed a high binding affinity. Additionally, co-expression and immunological analysis revealed that ABCA1 facilitates the immune infiltration of M2 macrophages in glioma, thereby stimulating tumor growth and aggravating the poor survival of patients. Altogether, we discovered that the ABCA1 transporter was involved in TMZ chemoresistance and the immune infiltration of M2 macrophages in glioma. Treatment with TMZ after ABCA1 knockdown enhances the chemosensitivity, suggesting that inhibition of ABCA1 may be a potential strategy for improving the therapeutic efficacy of gliomas.

FAM3 family genes are associated with prognostic value of human cancer: a pan-cancer analysis

Family with sequence similarity three member (FAM3) plays a crucial role in the malignant development of various cancers of human. However, there remains doubtful what specific role of FAM3 family genes in pan-cancer. Our study aimed to investigate the role of FAM3 family genes in prognosis, immune subtype, tumor immune microenvironment, stemness score, and anticancer drug sensitivity of pan-cancer. We obtained data from UCSC Xena GDC and CellMiner databases, and used them to study the correlation of the expression, survival, immune subtype, tumor microenvironment, stemness score, and anticancer drug sensitivity between FAM3 family genes with pan-cancer. Furthermore, we investigated the tumor cellular functions and clinical prognostic value FAMC3 in pancreatic cancer (PAAD) using cellular experiments and tissue microarray. Cell Counting Kit-8 (CCK-8), transwell invasion, wound-healing and apoptosis assays were performed to study the effect of FAM3C on SW1990 cells' proliferation, migration, invasion and apoptosis. Immunohistochemical staining was used to study the relationship between FAM3C expression and clinical characteristics of pancreatic cancer patients. The results revealed that FAM3 family genes are significantly differential expression in tumor and adjacent normal tissues in 7 cancers (CHOL, HNSC, KICH, LUAD, LUSC, READ, and STAD). The expression of FAM3 family genes were negatively related with the RNAss, and robust correlated with immune type, tumor immune microenvironment and drug sensitivity. The expression of FAM3 family genes in pan-cancers were significantly different in immune type C1 (wound healing), C2 (IFN-gamma dominant), C3 (inflammatory), C4 (lymphocyte depleted), C5 (immunologically quiet), and C6 (TGF-beta dominant). Meanwhile, overexpression FAM3C promoted SW1990 cells proliferation, migration, invasion and suppressed SW1990 cells apoptosis. While knockdown of FAM3C triggered opposite results. High FAM3C expression was associated with duodenal invasion, differentiation and liver metastasis. In summary, this study provided a new perspective on the potential therapeutic role of FAM3 family genes in pan-cancer. In particular, FAM3C may play an important role in the occurrence and progression of PAAD.

M2 macrophage marker CHI3L2 could serve as a potential prognostic and immunological biomarker in glioma by integrated single-cell and bulk RNA-Seq analysis

BACKGROUND

CHI3L2 plays a crucial role in multiple cancers, but its importance in glioma remains unclear. Hence, we comprehensively integrated bulk RNA-sequencing (RNA-seq), proteomics and single-cell RNA-seq (scRNA-seq) to determine the roles of CHI3L2 in gliomas.

METHODS

Bulk RNA-seq, proteomics and scRNA-seq data of CHI3L2 in glioma were obtained from online databases. The quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) were conducted to verify the CHI3L2 expression. Then, univariate and multivariate Cox regression analyses, Norman charts and gene set enrichment analysis (GSEA) were performed. Finally, the associations between CHI3L2 and tumor immunity were explored.

RESULTS

The expression of CHI3L2 was markedly higher in glioma cancers compared with normal tissues from analysis of the data of the Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets and as verified by GSE4290, GSE50161, qRT-PCR and IHC results (p < 0.05). High expression of CHI3L2 suggested poor overall survival (OS) prognosis in gliomas (p < 0.05). CHI3L2 might also serve as an independent predictor of OS for gliomas (p < 0.05) and we also constructed a Norman chart to predict these patients' survival prognosis with good performance. GSEA analysis showed that CHI3L2 might be involved with eight pathways in gliomas. Regarding tumor immunity, CHI3L2 was found to be significantly involved with immune cell infiltration levels of low-grade glioma, the tumor immune microenvironment, immune checkpoints and immune cells in both low-grade glioma and glioblastoma (p < 0.05). Additionally, scRNA-seq data for CHI3L2 in glioma from the TISCH2 website showed that CHI3L2 is mainly expressed in astrocytes, endothelial cells, CD8+ T cells, mono/macrophage cells, etc. CONCLUSIONS: CHI3L2 presents prognostic and immunological values in glioma, providing novel therapeutic targets for glioma patients.

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.

Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC

Background: SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure. Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database. Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment.

RepID represses megakaryocytic differentiation by recruiting CRL4A-JARID1A at DAB2 promoter

BACKGROUND

Megakaryocytes (MKs) are platelet precursors, which arise from hematopoietic stem cells (HSCs). While MK lineage commitment and differentiation are accompanied by changes in gene expression, many factors that modulate megakaryopoiesis remain to be uncovered. Replication initiation determinant protein (RepID) which has multiple histone-code reader including bromodomain, cryptic Tudor domain and WD40 domains and Cullin 4-RING E3 ubiquitin ligase complex (CRL4) recruited to chromatin mediated by RepID have potential roles in gene expression changes via epigenetic regulations. We aimed to investigate whether RepID-CRL4 participates in transcriptional changes required for MK differentiation.

METHODS

The PCR array was performed using cDNAs derived from RepID-proficient or RepID-deficient K562 erythroleukemia cell lines. Correlation between RepID and DAB2 expression was examined in the Cancer Cell Line Encyclopedia (CCLE) through the CellMinerCDB portal. The acceleration of MK differentiation in RepID-deficient K562 cells was determined by estimating cell sizes as well as counting multinucleated cells known as MK phenotypes, and by qRT-PCR analysis to validate transcripts of MK markers using phorbol 12-myristate 13-acetate (PMA)-mediated MK differentiation condition. Interaction between CRL4 and histone methylation modifying enzymes were investigated using BioGRID database, immunoprecipitation and proximity ligation assay. Alterations of expression and chromatin binding affinities of RepID, CRL4 and histone methylation modifying enzymes were investigated using subcellular fractionation followed by immunoblotting. RepID-CRL4-JARID1A-based epigenetic changes on DAB2 promoter were analyzed by chromatin-immunoprecipitation and qPCR analysis.

RESULTS

RepID-deficient K562 cells highly expressing MK markers showed accelerated MKs differentiation exhibiting increases in cell size, lobulated nuclei together with reaching maximum levels of MK marker expression earlier than RepID-proficient K562 cells. Recovery of WD40 domain-containing RepID constructs in RepID-deficient background repressed DAB2 expression. CRL4A formed complex with histone H3K4 demethylase JARID1A in soluble nucleus and loaded to the DAB2 promoter in a RepID-dependent manner during proliferation condition. RepID, CRL4A, and JARID1A were dissociated from the chromatin during MK differentiation, leading to euchromatinization of the DAB2 promoter.

CONCLUSION

This study uncovered a role for the RepID-CRL4A-JARID1A pathway in the regulation of gene expression for MK differentiation, which can form the basis for the new therapeutic approaches to induce platelet production. Video Abstract.

Schlafen 11 (SLFN11) Kills Cancer Cells Undergoing Unscheduled Re-replication

Schlafen 11 (SLFN11) is an increasingly prominent predictive biomarker and a molecular sensor for a wide range of clinical drugs: topoisomerases, PARP and replication inhibitors, and platinum derivatives. To expand the spectrum of drugs and pathways targeting SLFN11, we ran a high-throughput screen with 1,978 mechanistically annotated, oncology-focused compounds in two isogenic pairs of SLFN11-proficient and -deficient cells (CCRF-CEM and K562). We identified 29 hit compounds that selectively kill SLFN11-proficient cells, including not only previously known DNA-targeting agents, but also the neddylation inhibitor pevonedistat (MLN-4924) and the DNA polymerase α inhibitor AHPN/CD437, which both induced SLFN11 chromatin recruitment. By inactivating cullin-ring E3 ligases, pevonedistat acts as an anticancer agent partly by inducing unscheduled re-replication through supraphysiologic accumulation of CDT1, an essential factor for replication initiation. Unlike the known DNA-targeting agents and AHPN/CD437 that recruit SLFN11 onto chromatin in 4 hours, pevonedistat recruited SLFN11 at late time points (24 hours). While pevonedistat induced unscheduled re-replication in SLFN11-deficient cells after 24 hours, the re-replication was largely blocked in SLFN11-proficient cells. The positive correlation between sensitivity to pevonedistat and SLFN11 expression was also observed in non-isogenic cancer cells in three independent cancer cell databases (NCI-60, CTRP: Cancer Therapeutics Response Portal and GDSC: Genomic of Drug Sensitivity in Cancer). The present study reveals that SLFN11 not only detects stressed replication but also inhibits unscheduled re-replication induced by pevonedistat, thereby enhancing its anticancer efficacy. It also suggests SLFN11 as a potential predictive biomarker for pevonedistat in ongoing and future clinical trials.

IMOPAC: A web server for interactive multiomics and pharmacological analyses of patient-derived cancer cell lines

Large-scale multidimensional cancer genomic and pharmacological profiles have been created by several large consortium projects, including NCI-60, GDSC and DepMap, providing novel opportunities for data mining and further understanding of intrinsic therapeutic response mechanisms. However, it is increasingly challenging for experimental biologists, especially those without a bioinformatic background, to integrate, explore, and analyse these tremendous pharmacogenomics. To address this gap, IMOPAC, an interactive and easy-to-use web-based tool, was introduced to provide rapid visualizations and customizable functionalities on the basis of these three publicly available databases, which may reduce pharmacogenomic profiles from cell lines into readily understandable genetic, epigenetic, transcriptionomic, proteomic, metabolomic, and pharmacological events. The user-friendly query interface together with customized data storage enables users to interactively investigate and visualize multiomics alterations across genes and pathways and to link these alterations with drug responses across cell lines from diverse cancer types. The analyses in our portal include pancancer expression, drug-omics/pathway correlation, cancer subtypes, omics-omics (cis-/trans-regulation) correlation, fusion query analysis, and drug response prediction analysis. The comprehensive multiomics and pharmacogenomic analyses with simple clicking through IMOPAC will significantly benefit cancer precision medicine, contribute to the discoveries of potential biological mechanisms and facilitate pharmacogenomics mining in the identification of clinically actionable biomarkers for both basic researchers and clinical practitioners. IMOPAC is freely available at http://www.hbpding.com/IMOPAC.

Inhibition of CDK9 exhibits anticancer activity in hepatocellular carcinoma cells via targeting ribonucleotide reductase

Cyclin-dependent kinase 9 (CDK9) inhibitors are a novel category of anticancer treatment for cancers. However, their effects on hepatocellular carcinoma (HCC) are rarely investigated. Human ribonucleotide reductase (RR, which consists of RRM1 and RRM2 subunits) catalyzes the conversion of ribonucleoside diphosphate into 2'-deoxyribonucleoside diphosphate to maintain the homeostasis of nucleotide pools, which play essential roles in DNA synthesis and DNA repair. In this study, we identified that CDK9 protein expression in adjacent non-tumor tissues predicted HCC patients' overall and progression-free survivals. The anticancer activity of a CDK9-selective inhibitor, LDC000067, on HCC cells was positively associated with its ability to inhibit the expression of RRM1 and RRM2. LDC000067 downregulated RRM1 and RRM2 expression through post-transcriptional pathway. Specifically, LDC000067 triggered RRM2 protein degradation via multiple pathways, including proteasome-, lysosome-, and calcium-dependent pathways. Furthermore, CDK9 positively correlates with RRM1 or RRM2 expression in HCC patients, and the expressions of these three genes were associated with the higher infiltration of immune cells in HCC. Taken together, this study identified the prognostic relevance of CDK9 in HCC and the molecular mechanism for the anticancer effect of CDK9 inhibitors on HCC.

Single-cell and spatial transcriptomics reveal 5-methylcytosine RNA methylation regulators immunologically reprograms tumor microenvironment characterizations, immunotherapy response and precision treatment of clear cell renal cell carcinoma

Clear cell Renal Cell Carcinoma (ccRCC) is a highly heterogeneous disease, making it challenging to predict prognosis and therapy efficacy. In this study, we aimed to explore the role of 5-methylcytosine (m5C) RNA modification in ccRCC and its potential as a predictor for therapy response and overall survival (OS). We established a novel 5-methylcytosine RNA modification-related gene index (M5CRMRGI) and studied its effect on the tumor microenvironment (TME) using single-cell sequencing data for in-depth analysis, and verified it using spatial sequencing data. Our results showed that M5CRMRGI is an independent predictor of OS in multiple datasets and exhibited outstanding performance in predicting the OS of ccRCC. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in TME were observed between high- and low-M5CRMRGI groups. Single-cell/spatial transcriptomics revealed that M5CRMRGI could reprogram the distribution of tumor-infiltrating immune cells. Moreover, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade therapy of the high-risk group. We also predicted six potential drugs binding to the core target of the M5CRMRGI signature via molecular docking. Real-world treatment cohort data proved once again that high-risk patients were appropriate for immune checkpoint blockade therapy, while low-risk patients were appropriate for Everolimus. Our study shows that the m5C modification landscape plays a role in TME distribution. The proposed M5CRMRGI-guided strategy for predicting survival and immunotherapy efficacy, we reported here, might also be applied to more cancers other than ccRCC.

RepID represses megakaryocytic differentiation by recruiting CRL4A-JARID1A at DAB2 promoter

Background Megakaryocytes (MKs) are platelet precursors, which arise from hematopoietic stem cells (HSCs). While MK lineage commitment and differentiation are accompanied by changes in gene expression, many factors that modulate megakaryopoiesis remain to be uncovered. Replication origin binding protein (RepID) which has multiple histone-code reader including bromodomain, cryptic Tudor domain and WD40 domains and Cullin 4-RING ubiquitin ligase complex (CRL4) recruited to chromatin mediated by RepID have potential roles in gene expression changes via epigenetic regulations. We aimed to investigate whether RepID-CRL4 participates in transcriptional changes required for MK differentiation. Methods The PCR array was performed using cDNAs derived from RepID-proficient or RepID-deficient K562 erythroleukemia cell lines. Correlation between RepID and DAB2 expression was examined in the Cancer Cell Line Encyclopedia (CCLE) through the CellMinerCDB portal. The acceleration of MK differentiation in RepID-deficient K562 cells was determined by estimating cell sizes as well as counting multinucleated cells known as MK phenotypes, and by qRT-PCR analysis to validate transcripts of MK markers using phorbol 12-myristate 13-acetate (PMA)-mediated MK differentiation condition. Interaction between CRL4 and histone methylation modifying enzymes were investigated using BioGRID database, immunoprecipitation and proximity ligation assay. Alterations of expression and chromatin binding affinities of RepID, CRL4 and histone methylation modifying enzymes were investigated using subcellular fractionation followed by immunoblotting. RepID-CRL4-JARID1A-based epigenetic changes on DAB2 promoter were analyzed by chromatin-immunoprecipitation and qPCR analysis. Results RepID-deficient K562 cells highly expressing MK markers showed accelerated MKs differentiation exhibiting increases in cell size, lobulated nuclei together with reaching maximum levels of MK marker expression earlier than RepID-proficient K562 cells. Recovery of WD40 domain-containing RepID constructs in RepID-deficient background repressed DAB2 expression. CRL4A formed complex with histone H3K4 demethylase JARID1A in soluble nucleus and loaded to the DAB2 promoter in a RepID-dependent manner during proliferation condition. RepID, CRL4A, and JARID1A were dissociated from the chromatin during MK differentiation, leading to euchromatinization of the DAB2 promoter. Conclusion This study uncovered a role for the RepID-CRL4A-JARID1A pathway in the regulation of gene expression for MK differentiation, which can form the basis for the new therapeutic approaches to induce platelet production.

Microenvironment modulation by key regulators of RNA N6-methyladenosine modification in respiratory allergic diseases

BACKGROUND

RNA N6-methyladenosine (m6A) regulators are considered post-transcriptional regulators that affect several biological functions, and their role in immunity, in particular, is emerging. However, the role of m6A regulators in respiratory allergic diseases remains unclear. Therefore, we aimed to investigate the role of key m6A regulators in mediating respiratory allergic diseases and immune microenvironment infiltration characteristics.

METHODS

We downloaded gene expression profiles of respiratory allergies from the Gene Expression Omnibus (GEO) database and we performed hierarchical clustering, difference analysis, and construction of predictive models to identify hub m6A regulators that affect respiratory allergies. Next, we investigate the underlying biological mechanisms of key m6A regulators by performing PPI network analysis, functional enrichment analysis, and immune microenvironment infiltration analysis. In addition, we performed a drug sensitivity analysis on the key m6A regulator, hoping to be able to provide some implications for clinical medication.

RESULTS

In this study, we identified four hub m6A regulators that affect the respiratory allergy and investigated the underlying biological mechanisms. In addition, studies on the characteristics of immune microenvironment infiltration revealed that the expression of METTL14, METTL16, and RBM15B correlated with the infiltration of the mast and Th2 cells in respiratory allergy, and METTL16 expression was found to be significantly negatively correlated with macrophages for the first time (R = -0.53, P < 0.01). Finally, a key m6A regulator, METTL14, was screened by combining multiple algorithms. In addition, by performing a drug sensitivity analysis on METTL14, we hypothesized that it may play an important role in the improvement of allergic symptoms in the upper and lower airways with topical nasal glucocorticoids.

CONCLUSIONS

Our findings suggest that m6A regulators, particularly METTL14, play a crucial role in the development of respiratory allergic diseases and the infiltration of immune cells. These results may provide insight into the mechanism of action of methylprednisolone in treating respiratory allergic diseases.

CellMinerCDB: NCATS Is a Web-Based Portal Integrating Public Cancer Cell Line Databases for Pharmacogenomic Explorations

Major advances have been made in the field of precision medicine for treating cancer. However, many open questions remain that need to be answered to realize the goal of matching every patient with cancer to the most efficacious therapy. To facilitate these efforts, we have developed CellMinerCDB: National Center for Advancing Translational Sciences (NCATS; https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/), which makes available activity information for 2,675 drugs and compounds, including multiple nononcology drugs and 1,866 drugs and compounds unique to the NCATS. CellMinerCDB: NCATS comprises 183 cancer cell lines, with 72 unique to NCATS, including some from previously understudied tissues of origin. Multiple forms of data from different institutes are integrated, including single and combination drug activity, DNA copy number, methylation and mutation, transcriptome, protein levels, histone acetylation and methylation, metabolites, CRISPR, and miscellaneous signatures. Curation of cell lines and drug names enables cross-database (CDB) analyses. Comparison of the datasets is made possible by the overlap between cell lines and drugs across databases. Multiple univariate and multivariate analysis tools are built-in, including linear regression and LASSO. Examples have been presented here for the clinical topoisomerase I (TOP1) inhibitors topotecan and irinotecan/SN-38. This web application provides both substantial new data and significant pharmacogenomic integration, allowing exploration of interrelationships.

SIGNIFICANCE

CellMinerCDB: NCATS provides activity information for 2,675 drugs in 183 cancer cell lines and analysis tools to facilitate pharmacogenomic research and to identify determinants of response.

Identification of MDM2 as a prognostic and immunotherapeutic biomarker in a comprehensive pan-cancer analysis: A promising target for breast cancer, bladder cancer and ovarian cancer immunotherapy

BACKGROUND

The murine double minute 2 (MDM2) gene is a crucial factor in the development and progression of various cancer types. Multiple rigorous scientific studies have consistently shown its involvement in tumorigenesis and cancer progression in a wide range of cancer types. However, a comprehensive analysis of the role of MDM2 in human cancer has yet to be conducted.

METHODS

We used various databases, including TIMER2.0, TCGA, GTEx and STRING, to analyze MDM2 expression and its correlation with clinical outcomes, interacting genes and immune cell infiltration. We also investigated the association of MDM2 with immune checkpoints and performed gene enrichment analysis using DAVID tools.

RESULTS

The pan-cancer MDM2 analysis found that MDM2 expression and mutation status were observably different in 25 types of cancer tissue compared with healthy tissues, and prognosis analysis showed that there was a significant correlation between MDM2 expression and patient prognosis. Furthermore, correlation analysis showed that MDM2 expression was correlated with tumor mutational burden, microsatellite instability and drug sensitivity in certain cancer types. We found that there was an association between MDM2 expression and immune cell infiltration across cancer types, and MDM2 inhibitors might enhance the effect of immunotherapy on breast cancer, bladder cancer and ovarian cancer.

CONCLUSIONS

The first systematic pan-cancer analysis of MDM2 was conducted, and it demonstrated that MDM2 was a reliable prognostic biomarker and was closely related to cancer immunity, providing a potential immunotherapeutic target for breast cancer, bladder cancer and ovarian cancer.

A multi-omics analysis reveals CLSPN is associated with prognosis, immune microenvironment and drug resistance in cancers

BACKGROUND

Immunotherapy is effective only in limited patients. It is urgent to discover a novel biomarker to predict immune cells infiltration status and immunotherapy response of different cancers. CLSPN has been reported to play a pivotal role in various biological processes. However, a comprehensive analysis of CLSPN in cancers has not been conducted.

METHODS

To show the whole picture of CLSPN in cancers, a pan-cancer analysis was conducted in 9125 tumor samples across 33 cancer types by integrating transcriptomic, epigenomic and pharmacogenomics data. Moreover, the role of CLSPN in cancer was validated by CCK-8, EDU, colony formation and flow cytometry in vitro and tumor cell derived xenograft model in vivo.

RESULTS

CLSPN expression was generally upregulated in most cancer types and was significantly associated with prognosis in different tumor samples. Moreover, elevated CLSPN expression was closely correlated with immune cells infiltration, TMB (tumor mutational burden), MSI (microsatellite instability), MMR (mismatch repair), DNA methylation and stemness score across 33 cancer types. Enrichment analysis of functional genes revealed that CLSPN participated in the regulation of numerous signaling pathways involved in cell cycle and inflammatory response. The expression of CLSPN in LUAD patients were further analyzed at the single-cell level. Knockdown CLSPN significantly inhibited cancer cell proliferation and cell cycle related cyclin-dependent kinase (CDK) family and Cyclin family expression in LUAD (lung adenocarcinoma) both in vitro and in vivo experiments. Finally, we conducted structure-based virtual screening by modelling the structure of CHK1 kinase domain and Claspin phosphopeptide complex. The top five hit compounds were screened and validated by molecular docking and Connectivity Map (CMap) analysis.

CONCLUSION

Our multi-omics analysis offers a systematic understanding of the roles of CLSPN in pan-cancer and provides a potential target for future cancer treatment.

HTLV-1 bZIP factor impairs DNA mismatch repair system

Adult T-cell leukemia (ATL) is a peripheral T-cell malignancy caused by human T-cell leukemia virus type 1 (HTLV-1). Microsatellite instability (MSI) has been observed in ATL cells. Although MSI results from impaired mismatch repair (MMR) pathway, no null mutations in the genes encoding MMR factors are detectable in ATL cells. Thus, it is unclear whether or not impairment of MMR causes the MSI in ATL cells. HTLV-1 bZIP factor (HBZ) protein interacts with numerous host transcription factors and significantly contributes to disease pathogenesis and progression. Here we investigated the effect of HBZ on MMR in normal cells. The ectopic expression of HBZ in MMR-proficient cells induced MSI, and also suppressed the expression of several MMR factors. We then hypothesized that the HBZ compromises MMR by interfering with a transcription factor, nuclear respiratory factor 1 (NRF-1), and identified the consensus NRF-1 binding site at the promoter of the gene encoding MutS homologue 2 (MSH2), an essential MMR factor. The luciferase reporter assay revealed that NRF-1 overexpression enhanced MSH2 promoter activity, while co-expression of HBZ reversed this enhancement. These results supported the idea that HBZ suppresses the transcription of MSH2 by inhibiting NRF-1. Our data demonstrate that HBZ causes impaired MMR, and may imply a novel oncogenesis driven by HTLV-1.

Identification of immunotherapy-related lncRNA signature for predicting prognosis, immunotherapy responses and drug candidates in bladder cancer

BACKGROUND

Bladder cancer (BC) is one of the most common malignant diseases and the most common causes of cancer death worldwide. Immunotherapy has opened new avenues for precision treatment of bladder tumours, and immune checkpoint inhibitors (ICIs) have revolutionized the clinical treatment strategy of bladder tumours. In addition, long non-coding RNA (lncRNA) plays an important role in regulating tumour development and immunotherapy efficacy.

METHODS

We obtained genes with significant differences between anti-PD-L1 response and non-response from the Imvogor210 data set and combined with the bladder cancer expression data in the TCGA cohort to obtain immunotherapy-related lncRNA. Based on these lncRNAs, the prognostic risk model of bladder cancer was constructed and verified by GEO external data set. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analysed. We predicted the ceRNA network and performed molecular docking of key target proteins. The functional experiments verified the function of SBF2-AS1.

RESULTS

Three immunotherapy-related lncRNAs were identified as independent prognostic biomarkers for bladder cancer and a prognostic model of immunotherapy-related prognosis was constructed. Prognosis, immune cell infiltration, and immunotherapy efficacy were significantly different between high- and low-risk groups based on risk scores. Additionally, we established a ceRNA network of lncRNA(SBF2-AS1)-miRNA(has-miR-582-5p)-mRNA (HNRNPA2B1). Targeting the protein HNRNPA2B1 identified the top eight small molecule drugs with the highest affinity.

CONCLUSION

We developed a prognostic risk score model based on immune-therapy-related lncRNA, which was subsequently determined to be significantly associated with immune cell infiltration and immunotherapy response. This study not only helps to promote our understanding of immunotherapy-related lncRNA in the prognosis of BC, but also provides new ideas for clinical immunotherapy and the development of novel therapeutic drugs for patients.

Identification of osteosarcoma m6A-related prognostic biomarkers using artificial intelligence: RBM15

Osteosarcoma has the worst prognosis among malignant bone tumors, and effective biomarkers are lacking. Our study aims to explore m6A-related and immune-related biomarkers. Gene expression profiles of osteosarcoma and healthy controls were downloaded from multiple public databases, and their m6A-based gene expression was utilized for tumor typing using bioinformatics. Subsequently, a prognostic model for osteosarcoma was constructed using the least absolute shrinkage and selection operator and multivariate Cox regression analysis, and its immune cell composition was calculated using the CIBERSORTx algorithm. We also performed drug sensitivity analysis for these two genes. Finally, analysis was validated using immunohistochemistry. We also examined the RBM15 gene by qRT-PCR in an in vitro experiment. We collected routine blood data from 1738 patients diagnosed with osteosarcoma and 24,344 non-osteosarcoma patients and used two independent sample t tests to verify the accuracy of the CIBERSORTx analysis for immune cell differences. The analysis based on m6A gene expression tumor typing was most reliable using the two typing methods. The prognostic model based on the two genes constituting RNA-binding motif protein 15 (RBM15) and YTDC1 had a much lower survival rate for patients in the high-risk group than those in the low-risk group (P < 0.05). CIBERSORTx immune cell component analysis demonstrated that RBM15 showed a negative and positive correlation with T cells gamma delta and activated natural killer cells, respectively. Drug sensitivity analysis showed that these two genes showed varying degrees of correlation with multiple drugs. The results of immunohistochemistry revealed that the expression of these two genes was significantly higher in osteosarcoma than in paraneoplastic tissues. The results of qRT-PCR experiments showed that the expression of RBM15 was significantly higher in both osteosarcomas than in the control cell lines. Absolute lymphocyte value, lymphocyte percentage, hematocrit and erythrocyte count were lower in osteosarcoma than in the control group (P < 0.001). RBM15 and YTHDC1 can serve as potential prognostic biomarkers associated with m6A in osteosarcoma.

Computational drug repurposing by exploiting large-scale gene expression data: Strategy, methods and applications

De novo drug development is an extremely complex, time-consuming and costly task. Urgent needs for therapies of various diseases have greatly accelerated searches for more effective drug development methods. Luckily, drug repurposing provides a new and effective perspective on disease treatment. Rapidly increased large-scale transcriptome data paints a detailed prospect of gene expression during disease onset and thus has received wide attention in the field of computational drug repurposing. However, how to efficiently mine transcriptome data and identify new indications for old drugs remains a critical challenge. This review discussed the irreplaceable role of transcriptome data in computational drug repurposing and summarized some representative databases, tools and strategies. More importantly, it proposed a practical guideline through establishing the correspondence between three gene expression data types and five strategies, which would facilitate researchers to adopt appropriate strategies to deeply mine large-scale transcriptome data and discover more effective therapies.

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.

Comprehensive analysis of hypoxia-related genes for prognosis value, immune status, and therapy in osteosarcoma patients

Osteosarcoma is a common malignant bone tumor in children and adolescents. The overall survival of osteosarcoma patients is remarkably poor. Herein, we sought to establish a reliable risk prognostic model to predict the prognosis of osteosarcoma patients. Patients ' RNA expression and corresponding clinical data were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus databases. A consensus clustering was conducted to uncover novel molecular subgroups based on 200 hypoxia-linked genes. A hypoxia-risk models were established by Cox regression analysis coupled with LASSO regression. Functional enrichment analysis, including Gene Ontology annotation and KEGG pathway analysis, were conducted to determine the associated mechanisms. Moreover, we explored relationships between the risk scores and age, gender, tumor microenvironment, and drug sensitivity by correlation analysis. We identified two molecular subgroups with significantly different survival rates and developed a risk model based on 12 genes. Survival analysis indicated that the high-risk osteosarcoma patients likely have a poor prognosis. The area under the curve (AUC) value showed the validity of our risk scoring model, and the nomogram indicates the model's reliability. High-risk patients had lower Tfh cell infiltration and a lower stromal score. We determined the abnormal expression of three prognostic genes in osteosarcoma cells. Sunitinib can promote osteosarcoma cell apoptosis with down-regulation of KCNJ3 expression. In summary, the constructed hypoxia-related risk score model can assist clinicians during clinical practice for osteosarcoma prognosis management. Immune and drug sensitivity analysis can provide essential insights into subsequent mechanisms. KCNJ3 may be a valuable prognostic marker for osteosarcoma development.

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

Pancancer Analysis of the Prognostic and Immunotherapeutic Value of Progestin and AdipoQ Receptor 4

AdipoQ receptor 4 (PAQR4) belongs to the family of progestin and AdipoQ receptors. PAQR4 plays an oncogenic role in lung and breast cancer. However, systematic pancancer analyses of PAQR4 have not been performed. The purpose was to investigate the prognostic and immunological significance of PAQR4 across 31 tumor types. Data were obtained from the following sources: TCGA, GEO, UALCAN, TIMER, GEPIA2, KM plotter, and TISIDB databases. The results proved that PAQR4 expression was significantly elevatory in most cancer types. We then explored the utility of PAQR4 as a prognostic indicator across all cancers. Using Cox proportional risk regression models, it has been demonstrated that PAQR4 is an independent risk factor in. High PAQR4 expression was not associated with other prognostic indicators, including overall survival, disease-free interval, disease-specific survival, and progression-free period. Subsequently, we explored the immunological value of PAQR4 and found that PAQR4 expression significantly correlated with tumor mutational burden, microsatellite instability, neoantigen, and immune checkpoint genes in tumors. It also significantly negatively correlated with most tumors' ESTIMATE scores, indicating that PAQR4 can influence the cellular composition of the tumor microenvironment. Our findings suggest the immunotherapeutic potential of PAQR4 in tumors. Finally, we explored the role of PAQR4 in tumor drug resistance and found that PAQR4 expression affected the sensitivity to multiple chemotherapeutic agents. A significant role for PAQR4 in tumor immunity is evident in these studies, as well as its potential role in cancer diagnosis, prognosis, and treatment precision.