OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer

Systematic analysis of IGF2BP family members in non-small-cell lung cancer

BACKGROUND

The insulin-like growth factor-2 mRNA-binding proteins 1, 2, and 3 (IGF2BP1, IGF2BP2, and IGF2BP3) are known to be involved in tumorigenesis, metastasis, prognosis, and cancer immunity in various human cancers, including non-small cell lung cancer (NSCLC). However, the literature on NSCLC largely omits the specific context of lung squamous cell carcinoma (LUSC), an oversight we aim to address.

METHODS

Our study evaluated the differential expression of IGF2BP family members in tumors and normal tissues. Meta-analyses were conducted to assess the prognostic value of IGF2BPs in lung adenocarcinoma (LUAD) and LUSC. Additionally, correlations between IGF2BPs and tumor immune cell infiltration, mutation characteristics, chemotherapy sensitivity, and tumor mutation burden (TMB) were investigated. GSEA was utilized to delineate biological processes and pathways associated with IGF2BPs.

RESULTS

IGF2BP2 and IGF2BP3 expression were found to be upregulated in LUSC patients. IGF2BP2 mRNA levels were correlated with cancer immunity in both LUSC and LUAD patients. A higher frequency of gene mutations was observed in different IGF2BP1/2/3 expression groups in LUAD compared to LUSC. Meta-analyses revealed a significant negative correlation between overall survival (OS) and IGF2BP2/3 expression in LUAD patients but not in LUSC patients. GSEA indicated a positive association between VEGF and IGF2BP family genes in LUAD, while matrix metallopeptidase activity was inversely correlated with IGF2BP family genes in LUSC. Several chemotherapy drugs showed significantly lower IC50 values in high IGF2BP expression groups in both LUAD and LUSC.

CONCLUSION

Our findings indicated that IGF2BPs play different roles in LUAD and LUSC. This divergence highlights the need for tailored therapeutic strategies and prognostic tools, cognizant of the unique molecular profiles of LUAD and LUSC.

Potential association of HSPD1 with dysregulations in ribosome biogenesis and immune cell infiltration in lung adenocarcinoma: An integrated bioinformatic approach

BACKGROUND

Lung adenocarcinoma (LUAD) is a major histological subtype of lung cancer with a high mortality rate worldwide. Heat shock protein family D member 1 (HSPD1, also known as HSP60) is reported to be increased in tumor tissues of lung cancer patients compared with healthy control tissues.

OBJECTIVE

We aimed to investigate the roles of HSPD1 in prognosis, carcinogenesis, and immune infiltration in LUAD using an integrative bioinformatic analysis.

METHODS

HSPD1 expression in LUAD was investigated in several transcriptome-based and protein databases. Survival analysis was performed using the KM plotter and OSluca databases, while prognostic significance was independently confirmed through univariate and multivariate analyses. Integrative gene interaction network and enrichment analyses of HSPD1-correlated genes were performed to investigate the roles of HSPD1 in LUAD carcinogenesis. TIMER and TISIDB were used to analyze correlation between HSPD1 expression and immune cell infiltration.

RESULTS

The mRNA and protein expressions of HSPD1 were higher in LUAD compared with normal tissues. High HSPD1 expression was associated with male gender and LUAD with advanced stages. High HSPD1 expression was an independent prognostic factor associated with poor survival in LUAD patients. HSPD1-correlated genes with prognostic impact were mainly involved in aberrant ribosome biogenesis, while LUAD patients with high HSPD1 expression had low tumor infiltrations of activated and immature B cells and CD4+ T cells.

CONCLUSIONS

HSPD1 may play a role in the regulation of ribosome biogenesis and B cell-mediated immunity in LUAD. It could serve as a predictive biomarker for prognosis and immunotherapy response in LUAD.

A comparative study of the chloroplast genomes of five Lepidium species with high medicinal value

Plantgenomics is a rapidly developing field in medicinal plant research. This study analysed the relevant information of chloroplasts genome sequences of five medicinal plants from the genus Lepidium . We sequenced the complete chloroplast (cp) genomes of Lepidium apetalum Willd. and Lepidium perfoliatum Linnaeus., and assessed their genetic profiles against the reported profiles of Lepidium sativum Linnaeus., Lepidium meyenii Walp., and Lepidium virginicum Linn. We found that L. apetalum and L. perfoliatum possessed 130 distinct genes that included 85 protein-coding, 37 transfer RNA (tRNA), and eight ribosomal RNA (rRNA) genes. Our repeat analyses revealed that L. apetalum harboured 20 direct repeats, 16 palindrome repeats, 30 tandem repeats, and 87 simple sequence repeats, whereas, L. perfoliatum had 15 direct repeats, 20 palindrome repeats, four reverse repeats, 21 tandem repeats, and 98 simple sequence repeats. Using syntenic analysis, we also revealed a high degree of sequence similarity within the coding regions of Lepidium medicinal plant cp genomes, and a high degree of divergence among the intergenic spacers. Pairwise alignment and single-nucleotide polymorphism (SNP) examinations further revealed certain Lepidium -specific gene fragments. Codon usage analysis showed that codon 14 was the most frequently used codon in the Lepidium coding sequences. Further, correlation investigations suggest that L. apetalum and L. perfoliatum originate from similar genetic backgrounds. Analysis of codon usage bias of Lepidium cp genome was strongly influenced by mutation and natural selection. We showed that L. apetalum and L. perfoliatum will likely enhance breeding, species recognition, phylogenetic evolution, and cp genetic engineering of the Lepidium medicinal plants.

High Expression of TIMELESS Predicts Poor Prognosis: A Potential Therapeutic Target for Skin Cutaneous Melanoma

Background

Skin cutaneous melanoma (SKCM) is the most lethal skin cancer with an increasing incidence worldwide. The poor prognosis of SKCM urgently requires us to discover prognostic biomarkers for accurate therapy. As a regulator of DNA replication, TIMELESS (TIM) has been found to be highly expressed in various malignancies but rarely reported in SKCM. The objective of this study was to evaluate the relationship between TIM and SKCM tumorigenesis and prognosis.

Methods

We obtained RNA sequencing data from TCGA and GTEx to analyze TIM expression and differentially expressed genes (DEGs). Subsequently, GO/KEGG, GSEA, immune cell infiltration analysis, and protein-protein interaction (PPI) network were used to perform the functional enrichment analysis of TIM-related DEGs. Moreover, the receiver operating characteristic (ROC) curves, Cox regression analysis, Kaplan–Meier (K-M) analysis, and nomograms were applied to figure out the clinical significance of TIM in SKCM. In addition, we investigated the relationship between TIM promoter methylation and SKCM prognosis through the UALCAN database. Finally, the immunohistochemical (IHC) results of normal skin and SKCM were analyzed to determine expression differences.

Results

TIM was significantly elevated in various malignancies, including SKCM, and high expression of TIM was associated with poor prognosis. Moreover, a total of 402 DEGs were identified between the two distinct TIM expression groups, and functional annotation showed enrichment with positive regulation of cell cycle and classic oncogenic pathways in the high TIM expression phenotype, while keratinization pathways were negatively regulated and enriched. Further analysis showed that TIM was correlated with infiltration of multiple immune cells. Finally, IHC validated the differential expression of TIM in SKCM.

Conclusion

TIM might play a pivotal role in tumorigenesis of SKCM and is closely related to its prognosis.

A chemoproteoinformatics approach demonstrates that aspirin increases sensitivity to MEK inhibition by directly binding to RPS5

MEK inhibitors are among the most successful molecularly targeted agents used as cancer therapeutics. However, to treat cancer more efficiently, resistance to MEK inhibitor-induced cell death must be overcome. Although previous genetic approaches based on comprehensive gene expression analysis or RNAi libraries led to the discovery of factors involved in intrinsic resistance to MEK inhibitors, a feasible combined treatment with the MEK inhibitor has not yet been developed. Here, we show that a chemoproteoinformatics approach identifies ligands overcoming the resistance to cell death induced by MEK inhibition as well as the target molecule conferring this resistance. First, we used natural products, perillyl alcohol and sesaminol, which induced cell death in combination with the MEK inhibitor trametinib, as chemical probes, and identified ribosomal protein S5 (RPS5) as their common target protein. Consistently, trametinib induced cell death in RPS5-depleted cancer cells via upregulation of the apoptotic proteins BIM and PUMA. Using molecular docking and molecular dynamics (MD) simulations, we then screened FDA- and EMA-approved drugs for RPS5-binding ligands and found that acetylsalicylic acid (ASA, also known as aspirin) directly bound to RPS5, resulting in upregulation of BIM and PUMA and induction of cell death in combination with trametinib. Our chemoproteoinformatics approach demonstrates that RPS5 confers resistance to MEK inhibitor-induced cell death, and that aspirin could be repurposed to sensitize cells to MEK inhibition by binding to RPS5.

CBX7, a Potential Prognostic Biomarker in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a major type of NSCLC and has high morbidity and mortality. The identification of useful prognostic biomarkers for LUAD is important. CBX7 has been reported in various cancers yet its expression level and potential roles have not been fully understood.

Methods

GEPIA, Oncomine, TCGA, KM plotter and OSluca databases were used to explore the expression profile and prognostic effects of CBX7 mRNA expression in patients with LUAD. TIMER was used to explore the relationship between CBX7 and immune infiltrating cells. GSEA was used to further explore the potential biological process and pathways regulated by CBX7 in LUAD. Lastly, IHC detection of CBX7 in 95 samples was used to validate the result.

Results

We found CBX7 was downregulated in LUAD in GEPIA, Oncomine and TCGA databases. TCGA, KM plotter and OSluca databases suggested that CBX7 was associated with poor clinical outcomes and low survival rate. Using TIMER, we found that CBX7 might be associated with immune infiltration. Via gene set enrichment analysis, we found that tumor-associated biological processes and signaling pathways were enriched in the CBX7 downregulated group. Using clinical samples, we found that CBX7 protein has low expression in LUAD and was associated with poor survival.

Conclusion

CBX7 might serve as a promising biomarker and potential molecular target in LUAD.

In silico tools and databases for designing cancer immunotherapy

Immunotherapy is a rapidly growing therapy for cancer which have numerous benefits over conventional treatments like surgery, chemotherapy, and radiation. Overall survival of cancer patients has improved significantly due to the use of immunotherapy. It acts as a novel pillar for treating different malignancies from their primary to the metastatic stage. Recent preferments in high-throughput sequencing and computational immunology leads to the development of targeted immunotherapy for precision oncology. In the last few decades, several computational methods and resources have been developed for designing immunotherapy against cancer. In this review, we have summarized cancer-associated genomic, transcriptomic, and mutation profile repositories. We have also enlisted in silico methods for the prediction of vaccine candidates, HLA binders, cytokines inducing peptides, and potential neoepitopes. Of note, we have incorporated the most important bioinformatics pipelines and resources for the designing of cancer immunotherapy. Moreover, to facilitate the scientific community, we have developed a web portal entitled ImmCancer (https://webs.iiitd.edu.in/raghava/immcancer/), comprises cancer immunotherapy tools and repositories.

Thioredoxin reductase-1 levels are associated with NRF2 pathway activation and tumor recurrence in non-small cell lung cancer

Activating mutations in the KEAP1/NRF2 pathway characterize a subset of non-small cell lung cancer (NSCLC) associated with chemoresistance and poor prognosis. We herein evaluated the relationship between 64 oxidative stress-related genes and overall survival data from 35 lung cancer datasets. Thioredoxin reductase-1 (TXNRD1) stood out as the most significant predictor of poor outcome. In a cohort of NSCLC patients, high TXNRD1 protein levels correlated with shorter disease-free survival and distal metastasis-free survival post-surgery, including a subset of individuals treated with platinum-based adjuvant chemotherapy. Bioinformatics analysis revealed that NSCLC tumors harboring genetic alterations in the NRF2 pathway (KEAP1, NFE2L2 and CUL3 mutations, and NFE2L2 amplification) overexpress TXNRD1, while no association with EGFR, KRAS, TP53 and PIK3CA mutations was found. In addition, nuclear accumulation of NRF2 overlapped with upregulated TXNRD1 protein in NSCLC tumors. Functional cell assays and gene dependency analysis revealed that NRF2, but not TXNRD1, has a pivotal role in KEAP1 mutant cells' survival. KEAP1 mutants overexpress TXNRD1 and are less susceptible to the cytotoxic effects of the TXNRD1 inhibitor auranofin when compared to wild-type cell lines. Inhibition of NRF2 with siRNA or ML-385, and glutathione depletion with buthionine-sulfoximine, sensitized KEAP1 mutant A549 cells to auranofin. NRF2 knockdown and GSH depletion also augmented cisplatin cytotoxicity in A549 cells, whereas auranofin had no effect. In summary, these findings suggest that TXNRD1 is not a key determinant of malignant phenotypes in KEAP1 mutant cells, although this protein can be a surrogate marker of NRF2 pathway activation, predicting tumor recurrence and possibly other aggressive phenotypes associated with NRF2 hyperactivation in NSCLC.

The regulation of CPNE1 ubiquitination by the NEDD4L is involved in the pathogenesis of non-small cell lung cancer

Our previous studies revealed that oncogene CPNE1 is positively correlated with the occurrence, TNM stage, lymph node metastasis, and distant metastasis of non-small-cell lung cancer (NSCLC), and it could be regulated by micro RNAs. But no direct role of post-translational modification of CPNE1 in NSCLC has been reported. This study confirms that CPNE1 is degraded by two pathways: the ubiquitin-proteasome pathway and the autophagy-lysosome pathway. CPNE1 binds with the ubiquitin molecule via its K157 residue. Moreover, we determined that the ubiquitin ligase NEDD4L can mediate the ubiquitination of CPNE1 and promote its degradation. In addition, we find that NEDD4L knockdown promotes the proliferation and metastasis of NSCLC cells by regulating CPNE1 in vitro and vivo. This study aims to further investigate the mechanism of CPNE1 ubiquitination in the occurrence and development of NSCLC and provide a new potential target for NSCLC treatment.

CTHRC1 expression is a novel shared diagnostic and prognostic biomarker of survival in six different human cancer subtypes

According to the previous reports, the collagen triple helix repeat containing 1 (CTHRC1) causes tumorigenesis by modulating the tumor microenvironment, however, the evidence is limited to a few human cancer subtypes. In the current study, we analyzed and validated the CTHRC1 expression variations in 24 different human cancer tissues paired with normal tissues using publically available databases. We observed that CTHRC1 was overexpressed in all the 24 major subtypes of human cancers and its overexpression was significantly associated with the reduced overall survival (OS) duration of head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), stomach adenocarcinoma (STAD), and Uterine corpus endometrial carcinoma (UCEC). This implies that CTHRC1 plays a significant role in the development and progression of these cancers. We further noticed that CTHRC1 was also overexpressed in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of CTHRC1 associated genes in seven diverse pathways. We also explored few interesting correlations between CTHRC1 expression and promoter methylation, genetic alterations, CNVs, CD8+ T immune cells infiltration, and tumor purity. In conclusion, CTHRC1 can serve as a shared diagnostic and prognostic biomarker in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features.

Lin28A promotes the proliferation and stemness of lung cancer cells via the activation of mitogen-activated protein kinase pathway dependent on microRNA let-7c

Background

Among patients with lung cancer, metastatic and relapsed cases account for the largest proportion of disease-associated deaths. Tumor metastasis and relapse are believed to originate from cancer stem cells (CSCs), which have the capacity to be highly proliferative and invasive. In our previous studies, we established a conditional basement membrane extract-based (BME-based) 3-dimensional (3D) culture system to mimic the tumor growth environment in vivo and further amplified lung cancer stem cells (LCSCs) in our system. However, the molecular mechanisms of LCSC amplification and development in our 3D culture system have not been fully uncovered.

Method

We established the conditional 3D culture system to amplify LCSCs in other lung cancer cell lines, followed by examining the expression of Lin28A and let-7 microRNAs in them. We also explored the expression of Lin28A and let-7 microRNAs in LCSCs from clinical lung cancer tissue samples and even analyzed the correlation of Lin28A/let-7c and patients’ survival outcomes. We further constructed A549 cells either knockdown of Lin28A or overexpression of let-7c, followed by investigating stemness marker gene expression, and stemness phenotypes including mammosphere culture, cell migration and invasion in vitro, as well as tumorigenicity in vivo.

Results

Here, we observed that Lin28A/let-7c was dysregulated in LCSCs in both the 3D culture system and lung cancer tissues. Further, the abnormal expression of Lin28A/let-7c was correlated with poor survival outcomes. Via the construction of A549 cells with let-7c over-expression, we found that let-7c inhibited the maintenance of LCSC properties, while the results of Lin28A knockdown showed that Lin28A played a critical role in the enrichment and proliferation of LCSCs via mitogen-activated protein kinase (MAPK) signaling pathway. Importantly, we found that LCSCs with knockdown of Lin28A or over-expression of let-7c exhibited inhibited carcinogenesis and disrupted expansion in vivo.

Conclusions

Our study uncovered the functions and mechanisms of the Lin28A/let-7c/MAPK signaling pathway in promoting the proliferation and cancer stemness of LCSCs, which might be a potential therapeutic target for reducing and even eliminating LCSCs in the future.

Computational resources for identification of cancer biomarkers from omics data

Cancer is one of the most prevailing, deadly and challenging diseases worldwide. The advancement in technology led to the generation of different types of omics data at each genome level that may potentially improve the current status of cancer patients. These data have tremendous applications in managing cancer effectively with improved outcome in patients. This review summarizes the various computational resources and tools housing several types of omics data related to cancer. Major categorization of resources includes-cancer-associated multiomics data repositories, visualization/analysis tools for omics data, machine learning-based diagnostic, prognostic, and predictive biomarker tools, and data analysis algorithms employing the multiomics data. The review primarily focuses on providing comprehensive information on the open-source multiomics tools and data repositories, owing to their broader applicability, economic-benefit and usability. Sections including the comparative analysis, tools applicability and possible future directions have also been discussed in detail. We hope that this information will significantly benefit the researchers and clinicians, especially those with no sound background in bioinformatics and who lack sufficient data analysis skills to interpret something from the plethora of cancer-specific data generated nowadays.

Increased Expression of TICRR Predicts Poor Clinical Outcomes: A Potential Therapeutic Target for Papillary Renal Cell Carcinoma

Background: Papillary renal cell carcinoma (PRCC), although the second-most common type of renal cell carcinoma, still lacks specific biomarkers for diagnosis, treatment, and prognosis. TopBP1-interacting checkpoint and replication regulator (TICRR) is a DNA replication initiation regulator upregulated in various cancers. We aimed to evaluate the role of TICRR in PRCC tumorigenesis and prognosis.

Methods: Based on the Kidney Renal Papillary cell carcinoma Project (KIRP) on The Cancer Genome Atlas (TCGA) database, we determined the expression of TICRR using the Wilcoxon rank sum test. The biological functions of TICRR were evaluated using the Metascape database and Gene Set Enrichment Analysis (GSEA). The association between TICRR and immune cell infiltration was investigated by single sample GSEA. Logistic analysis was applied to study the correlation between TICRR expression and clinicopathological characteristics. Finally, Cox regression analysis, Kaplan–Meier analysis, and nomograms were used to determine the predictive value of TICRR on clinical outcomes in PRCC patients.

Results:TICRR expression was significantly elevated in PRCC tumors (P < 0.001). Functional annotation indicated enrichment with negative regulation of cell division, cell cycle, and corresponding pathways in the high TICRR expression phenotype. High TICRR expression in PRCC was associated with female sex, younger age, and worse clinical stages. Cox regression analysis revealed that TICRR was a risk factor for overall survival [hazard ratio (HR): 2.80, P = 0.002], progression-free interval (HR: 2.86, P < 0.001), and disease-specific survival (HR: 7.03, P < 0.001), especially in patients with male sex, age below 60 years, clinical stages II–IV and clinical T stage T1–T2.

Conclusion: Increased TICRR expression in PRCC might play a role in tumorigenesis by regulating the cell cycle and has prognostic value for clinical outcomes.

A signature of tumor DNA repair genes associated with the prognosis of surgically-resected lung adenocarcinoma

Background

Lung cancer has the highest morbidity and mortality of cancers worldwide. Lung adenocarcinoma (LUAD) is the most common pathological subtype of lung cancer and surgery is its most common treatment. The dysregulated expression of DNA repair genes is found in a variety of cancers and has been shown to affect the origin and progression of these diseases. However, the function of DNA repair genes in surgically-treated LUAD is unclear.

Methods

We sought to determine the association between the signature of DNA repair genes for patients with surgical LUAD and their overall prognosis. We obtained gene expression data and corresponding clinical information of LUAD from The Cancer Genome Atlas (TCGA) database. The differently expressed DNA repair genes of surgically-treated LUAD and normal tissues were identified using the Wilcoxon rank-sum test. We used uni- and multivariate Cox regression analyses to shrink the aberrantly expressed genes, which were then used to construct the prognostic signature and the risk score formula associated with the independent prognosis of surgically-treated LUAD. We used Kaplan-Meier and Cox hazard ratio analyses to confirm the diagnostic and prognostic roles. Two validation sets (GSE31210 and GSE37745) were downloaded from the Gene Expression Omnibus (GEO) and were used to externally verify the prognostic value of the signature. OSluca online database verifies the hazard ratio for the DNA repair genes by which the signature was constructed. We investigated the correlation between the signature of the DNA repair genes and the clinical parameters. The potential molecular mechanisms and pathways of the prognostic signature were explored using Gene Set Enrichment Analysis (GSEA).

Results

We determined the prognostic signature based on six DNA repair genes (PLK1, FOXM1, PTTG1, CCNO, HIST3H2A, and BLM) and calculated the risk score based on this formula. Patients with surgically-treated LUAD were divided into high-risk and low-risk groups according to the median risk score. The high-risk group showed poorer overall survival than the low-risk group; the signature was used as an independent prognostic indicator and had a greater prognostic value in surgically-treated LUAD. The prognostic value was replicated in GSE31210 and GSE37745. OSluca online database analysis shows that six DNA repair genes were associated with poor prognosis in most lung cancer datasets. The prognostic signature risk score correlated with the pathological stage and smoking status in surgically-treated LUAD. The GSEA of the risk signature in high-risk patients showed pathways associated with the cell cycle, oocyte meiosis, mismatch repair, homologous recombination, and nucleotide excision repair.

Conclusions

A six-DNA repair gene signature was determined using TCGA data mining and GEO data verification. The gene signature may serve as a novel prognostic biomarker and therapeutic target for surgically-treated LUAD.

Development of an Immune-Related Risk Signature for Predicting Prognosis in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LSCC) is the most common subtype of non-small cell lung cancer. Immunotherapy has become an effective treatment in recent years, while patients showed different responses to the current treatment. It is vital to identify the potential immunogenomic signatures to predict patient' prognosis. The expression profiles of LSCC patients with the clinical information were downloaded from TCGA database. Differentially expressed immune-related genes (IRGs) were extracted using edgeR algorithm, and functional enrichment analysis showed that these IRGs were primarily enriched in inflammatory- and immune-related processes. "Cytokine-cytokine receptor interaction" and "PI3K-AKT signaling pathway" were the most enriched KEGG pathways. 27 differentially expressed IRGs were significantly correlated with the overall survival (OS) of patients using univariate Cox regression analysis. A prognostic risk signature that comprises seven IRGs (GCCR, FGF8, CLEC4M, PTH, SLC10A2, NPPC, and FGF4) was developed with effective predictive performance by multivariable Cox stepwise regression analysis. Most importantly, the signature could be an independent prognostic predictor after adjusting for clinicopathological parameters, and also validated in two independent LSCC cohorts (GSE4573 and GSE17710). Potential molecular mechanisms and tumor immune landscape of these IRGs were investigated through computational biology. Analysis of tumor infiltrating lymphocytes and immune checkpoint molecules revealed distinct immune landscape in high- and low-risk group. The study was the first time to construct IRG-based immune signature in the recognition of disease progression and prognosis of LSCC patients.