Current Cancer Drug Targets - Volume 24, Issue 1, 2024

Lung cancer is one of the most lethal malignancies, with non-small cell lung cancer (NSCLC) being the most common histologic subtype. Metastasis leads to poor prognosis for patients with cancer. Tumor cells leave the tumor lesions, invade the surrounding stroma, and enter the bloodstream as circulating tumor cells (CTCs). The development of CTCs is the beginning of metastasis. The internal environment in which tumor cells grow and survive is called the tumor microenvironment (TME). It includes tumor cells, fibroblasts, immune cells, and the extracellular matrix. The TME is complex and dynamic. Moreover, the TME plays an important role in tumor development and metastasis and significantly impacts therapeutic outcomes. Immune checkpoint blockade (ICB) aims to inhibit the interaction of ligands with their corresponding receptors. ICB has the function of restoring the anti-tumor effect of immune cells. This review examines how TME interacts with CTCs, allowing CTCs to evade immunity and facilitating CTC metastasis. TME not only affects the progression of tumor metastasis but also interacts with tumor cells, which may affect the efficacy of immunotherapy.

Background: Heat shock 70kDa protein 5 (HSPA5), also known as GRP78, is widely expressed in most malignant cells and has been shown to have a significant role in the spread of most malignancies by transferring them to the cell membrane. High-level HSPA5 may serve as an independent prognostic marker for various malignancies due to its ability to accelerate tumor growth and migration, inhibit cell apoptosis and closely connect to prognosis. Therefore, it is crucial to examine HSPA5 using pan-cancer research, which might result in the discovery of novel cancer treatment targets. Methods: The GTEx and TCGA databases have both provided evidence of the expression of various amounts of HSPA5 in various tissues. The Clinical Proteomics Tumor Analysis Consortium (CPTAC) evaluated the levels of HSPA5 protein expression, while qPCR investigations also evaluated the expression of HSPA5 mRNA in certain tumors. HSPA5 was studied using the Kaplan-Meier method to examine how it influences overall survival and disease-free survival in malignancies. GEPIA2 was used to investigate the correlation between HSPA5 expression and the clinical stage of cancer. The tumor-immune system interaction database (TISIDB) examined the expression of HSPA5 in association with molecular and tumor immune subtypes. The co-expressed genes of HSPA5 were extracted from the STRING database, and the top 5 co-expressed genes of HSPA5 in 33 cancers were identified using the TIMER database. Further research examined the relationship between tumor mutations and HSPA5. Microsatellite Instability (MSI) and Tumor Mutation Burden (TMB) were the primary areas of interest. The association between HSPA5 mRNA expression and immune infiltration was also explored using the TIMER database. Additionally, through the Linkedomics database, we examined the enrichment of GO and KEGG for HSPA5 in glioblastoma. Finally, the Cluster Analyzer tool was used to carry out a GSEA functional enrichment investigation. Results: HSPA5 mRNA expression was found to be greater in all 23 tumor tissues than in the equivalent normal tissues, and high HSPA5 expression appeared to be strongly related to a poor prognosis in the majority of cancers, as observed by survival plots. In the tumour clinical stage display map, HSPA5 showed differential expression in most tumours. HSPA5 is strongly associated with Tumor Mutation Burden (TMB) and Microsatellite Instability (MSI). Cancer-associated Fibroblasts (CAFs) infiltration was strongly associated with HSPA5, as were nine immunological subtypes of malignancy and seven molecular subtypes of malignancy. According to the results of GO and KEGG enrichment analyses, HSPA5 in GBM is mostly involved in neutrophil-mediated immunological and collagen metabolic activities. Additionally, GSEA enrichment analyses of HSPA5 and associated genes demonstrated a substantial link between HSPA5 and the immunological milieu of tumors, cell division and nervous system regulation. By using qPCR, we were able to further corroborate the enhanced expression in the GBM, COAD, LUAD and CESC cell lines. Conclusion: Our bioinformatics research leads us to hypothesize that HSPA5 may be involved in immune infiltration as well as tumor growth and progression. Additionally, it was found that differentially expressed HSPA5 is linked to a poor prognosis for cancer, with the neurological system, the tumor immunological microenvironment and cytokinesis being potential contributing factors. As a result, HSPA5 mRNA and the associated protein might be used as therapeutic targets and possible prognostic markers for a range of malignancies.

Background: Prostate tumor overexpressed-1 (PTOV1) is a conserved oncogenic adaptor protein associated with cancer progression and may be an independent prognostic marker for several malignancies. Consequently, using pan-cancer research to explore the significance of PTOV1 is valuable, and may reveal novel targets for cancer treatment. Methods: A comprehensive bioinformatics analysis of PTOV1 was performed. The qRT-PCR was utilized to confirm the aberrant PTOV1 expression in several cancer cell lines. Results: We observed that PTOV1 mRNA expression was high in 18 cancer tissues and was thereafter associated with poor survival prognosis in a range of malignancies. The immune subtypes of 14 malignancies and the molecular subtypes of six malignancies were related to PTOV1. A substantial association between PTOV1 and immune checkpoint (ICP) genes was also observed. Tumor mutational burden (TMB), microsatellite instability (MSI), and DNA methylation analyses indicated that PTOV1 acts as a cancer-promoting agent in a series of tumors. In addition, an enrichment study of PTOV1 and related genes revealed that RNA splicing may be responsible for the involvement of PTOV1 in cancers. Lastly, we also verified that PTOV1 expression was elevated in bladder cancer, breast cancer, CESC, LIHC cell lines via qRT-PCR. Conclusion: Our bioinformatics research indicated that PTOV1 may be involved in tumor immunity. Furthermore, differentially expressed PTOV1 was found to be related to poor prognosis in cancers, and RNA splicing may be the specific mechanism for this effect. Therefore, PTOV1 mRNA and the corresponding protein may function as potential prognostic indicators and therapeutic targets in various cancers.

Aim: The study aimed to explore the effect of metabolism on lung cancer. Background: The tumor microenvironment is largely influenced by metabolism, tightly involved in tumor progression. Objective: We try to investigate the effect of tumor metabolism terms on non-small cell lung cancer (NSCLC) prognosis, drug and immunotherapy sensitivity, as well as its underlying mechanisms. Methods: All the data was obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. R software was used to perform all statistical analyses and plots. Results: This study conducted 21 metabolism statuses in NSCLC to identify their underlying roles. We found that alpha-linolenic acid metabolism, sphingolipid metabolism, glycerophospholipid metabolism, fatty acid degradation, linoleic acid metabolism, primary bile acid biosynthesis, and fatty acid metabolism were protective factors for NSCLC. Next, we constructed a prognosis model based on primary bile acid biosynthesis, glycerophospholipid, and sphingolipid metabolism. Results in the present study showed that our model could effectively predict patients' prognosis in both training and validation cohorts. A clinical correlation revealed that patients at high-risk exhibited more progressive clinical characteristics. Biological enrichment indicated that MYC targets, E2F targets, mTORC1 signaling, G2/M checkpoint, and epithelial-mesenchymal transition were activated in the high-risk group. Immune relation analysis showed that risk score positively correlated with Th2 cells, yet a negative correlation with CD56 bright NK, Th17, mast and CD8+ T cells. Moreover, our model was related to NSCLC patients' sensitivity to immunotherapy and chemotherapy. Ultimately, eight characteristic genes were identified to distinguish the patients' risk group in the real application. Conclusions: The model we developed is a useful tool to predict NSCLC patients' prognosis and is associated with the sensitivity of immunotherapy and chemotherapy. Meanwhile, our results can guide the following metabolism-related studies in NSCLC.

Background: Triple-negative breast cancer (TNBC) has the poorest prognosis among all breast cancer subtypes. While several tumor types are excepted to have a curative response to immunotherapy through the AT-rich interaction domain 1A (ARID1A) gene, its role in TNBC remains unclear. Methods: The expression of the ARID1A gene and immune infiltration in TNBC were analyzed by way and function enrichment analysis. Additionally, 27 gene mutations, including ARID1A mutation, were detected in paraffin-embedded TNBC specimens and normal breast specimens using Next Generation Sequencing (NGS). Immunohistochemical staining was employed to detect the expression of AIRD1A, TP53, Ki67, CD4, CD8, and PD-L1 proteins in TNBC and the adjacent normal tissue samples. Results: The bioinformatics analysis revealed that ARID1A was mutated in TNBC and significantly associated with tumor immune infiltration. NGS analysis showed a high mutation rate of ARID1A (35%) in TNBC, but the mutation status of ARID1A was not associated with age at onset, lymph node metastasis, pathological grade, or Ki67 index. Low expression or loss of AIRD1A was more commonly observed in TNBC tissues (36/108) as compared to normal tissues (3/25). Positive expression of CD8 and PD-L1 was observed in TNBC tissues with low ARID1A expression. ARID1A mutation was associated with low protein expression, and patients with ARID1A mutation or low protein expression had shorter progression-free survival. Conclusion: The ARID1A mutation and low expression are associated with poor prognosis and high immune infiltration in TNBC, and might be biomarkers for TNBC prognosis and immunotherapy efficacy.

Background: Ubiquitin ligases (E3s) play an important role in multiple cancers. Methods: The open-accessed expression profile and clinical information was downloaded from the TARGET database. The analysis was performed using R software. Results: In this study, we comprehensively investigated the role of E3s in osteosarcomas (OS). We found that among all these E3s, UBR5 is a risk factor for OS. Considering that UBR5 has not been reported in previous studies focused on OS, we selected it for further analysis. Interestingly, we found that UBR5 had no significant effect on immune cell infiltration but a remarkable effect on immune function. Moreover, we divided the patients into “immune activation” and “immune exhaustion” types. KM survival curves indicated that the patients in the “immune exhaustion” types had a worse survival performance. Further, we identified the molecules involved in immune function and significantly correlated with UBR5. The biological enrichment analysis and prognosis model were then conducted based on these genes. Results indicated that the patients in the high-risk group had a worse survival performance, and underlying biological differences between high and low-risk patients were also explored. Ultimately, the effect pattern of UBR5 in pan-cancer was also explored. Conclusion: In summary, our study comprehensively explored the role of UBR5 in OS, as well as its effect on the immune microenvironment, which might be an underlying therapy target.

Background: Necroptosis is correlated with the development, prognosis, and treatment of tumors. However, the function of necroptosis-associated genes (NRGs) in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC) remains unclear. Methods: In this study, 1210 NSCLC samples were classified into different subtypes based on the expression of 66 NRGs by unsupervised clustering analysis, and further analyzed the TME characteristics of these subtypes. In addition, we identified common differentially expressed genes (co-DEGs) in NRG subtypes and constructed the NRG score using principal component analysis (PCA) to assess the NRG-mediated TME characteristics of patients with NSCLC. Results: Using unsupervised cluster analysis, 1210 NSCLC samples were divided into NRGcluster A and B subtypes. The NRGcluster B survived significantly better than the NRGcluster A. TME characterization revealed that NRGcluster B was upregulated in immune and stromal signaling activation, whereas NRGcluster A was upregulated in oncogenic signaling. The NRG score constructed based on co-DEGs of the two NRG-related subtypes was positively correlated with immune cell infiltration and negatively correlated with the number of cancer stem cells (CSCs) and tumor mutational burden (TMB). In addition, survival was significantly worse in the low-NRG-score group compared to the high-NRG-score group. Finally, the assessment of immunotherapeutic efficacy showed that immunotherapeutic response was significantly worse in the low-NRG-score group compared to the high- NRG-score group. Conclusion: This research reveals that NRGs are associated with the complexity and diversity of TME in NSCLC. Adopting the NRG score to quantitatively assess NRG-mediated TME in individual patients with NSCLC may help in planning clinical treatment strategies.

The capacity of cancer cells for abnormal growth and metastasis has made it difficult to find a cure for tumor. Both males and females suffer from lung tumors, and physicians still deem them incurable. The initiation and development of lung tumors can be forced by genomic mutations. Wnt is a critical pathway for regulating growth, differentiation and migration. However, its oncogenic function has been observed in lung cancer. Wnt is able to increase the proliferation of lung tumors. The metastasis potential of lung tumors can be accelerated by Wnt/EMT axis. Overexpression of Wnt/β-catenin prevents chemotherapy-mediated cell death in lung tumors. This pathway promotes cancer stem cell features in lung tumors which induce radioresistance. Anti-cancer agents, such as curcumin, are able to inhibit Wnt in lung tumor treatment. Wnt interaction with other factors in lung tumors is essential in controlling biological behavior, and non-coding RNA transcripts are the most well-known ones. It can be concluded from the current study that Wnt is an important regulator of lung tumorigenesis, and the translation of these findings into the clinic is vital.

OSCC (Oral Squamous Cell Carcinoma) is a major health challenge in many parts of the world. It occurs most commonly in males and is associated with tobacco, pan, or areca nut consumption. One of the major challenges associated with the management of OSCC is late diagnosis. As a result, the treatment required is more aggressive, expensive, and has poor prognostic value. On the other hand, early diagnosis of OSCC can be life-saving with less aggressive treatment and a better prognosis. A diagnostic method for early diagnosis of OSCC is greatly needed. A lot of research efforts have been made to identify biomarkers that can act as tools to classify the tumor status of the patient. Various biological fluids and tissues have been explored for such studies. Saliva appears to be the most attractive biological sample with many potential advantages over other matrices such as blood or tissue. Saliva as a diagnostic fluid has the advantage of ample availability, being non-invasive and being in the vicinity of the tumor, and having a less complex composition. Our paper provides an updated review of the state of the art of research in the area of salivary biomarkers for oral squamous cell carcinoma. The paper gives an account of methods for saliva collection, followed by a brief description of various protein biomarkers discovered to date, along with their status quo.