Transcriptome evolution from breast epithelial cells to basal-like tumors

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Molecular profiling of core immune-escape genes highlights LCK as an immune-related prognostic biomarker in melanoma

The tumor microenvironment is complicated and continuously evolving. This study was devoted to the identification of potential prognostic biomarkers based on the tumor microenvironment associated with immunotherapy for melanoma. This study integrates a couple of melanoma single cell and transcriptome sequencing datasets and performs a series of silico analyses as nicely as validation of molecular biology techniques. A core set of immune escape related genes was identified through Lawson et al. and the ImmPort portal. The differential proteins were identified through the cBioPortal database. Regression analysis was used to profile independent prognostic factors. Correlation with the level of immune cell infiltration was evaluated by multiple algorithms. The capacity of LCK to predict response was assessed in two independent immunotherapy cohorts. High LCK expression is associated with better prognosis, high levels of TILs and better clinical staging. Pathway analysis showed that high expression of LCK was significantly associated with activation of multiple tumor pathways as well as immune-related pathways. LCK expression tends to be higher in immunotherapy-responsive patients and those with lower IC50s treated with chemotherapeutic agents. RT-qPCR detected that LCK expression was significantly upregulated in melanoma cell lines. Single-cell transcriptome analysis showed that LCK was specifically highly expressed on T cells. CellChat analysis confirmed that LCK in C2 subpopulations and T cell subpopulations exerted immune promotion between cells by binding to CD8 receptors. In conclusion, LCK is a reliable biomarker for melanoma and will contribute to its immunotherapy.

Molecular signatures of in situ to invasive progression for basal-like breast cancers: An integrated mouse model and human DCIS study

Ductal carcinoma in situ (DCIS) of the breast is a non-obligate precursor of Invasive Ductal Carcinoma (IDC) and thus the identification of features that may predict DCIS progression would be of potential clinical value. Experimental mouse models can be used to address this challenge by studying DCIS-to-IDC biology. Here we utilize single cell RNA sequencing (scRNAseq) on the C3Tag genetically engineered mouse model that forms DCIS-like precursor lesions and for which many lesions progress into end-stage basal-like molecular subtype IDC. We also perform bulk RNAseq analysis on 10 human synchronous DCIS-IDC pairs comprised of estrogen receptor (ER) positive and ER-negative subsets and utilize 2 additional public human DCIS data sets for comparison to our mouse model. By identifying malignant cells using inferred DNA copy number changes from the murine C3Tag scRNAseq data, we show the existence of cancer cells within the C3Tag pre-DCIS, DCIS, and IDC-like tumor specimens. These cancer cells were further classified into proliferative, hypoxic, and inflammatory subpopulations, which change in frequency in DCIS versus IDC. The C3Tag tumor progression model was also associated with increase in Cancer-Associated Fibroblasts and decrease in activated T cells in IDC. Importantly, we translate the C3Tag murine genomic findings into human DCIS where we find common features only with human basal-like DCIS, suggesting there are intrinsic subtype unique DCIS features. This study identifies several tumor and microenvironmental features associated with DCIS progression and may also provide genomic signatures that can identify progression-prone DCIS within the context of human basal-like breast cancers.

Identification of Biomarkers Related to Regulatory T Cell Infiltration in Oral Squamous Cell Carcinoma Based on Integrated Bioinformatics Analysis

Background

Oral squamous cell carcinoma (OSCC) is one of the most prevalent malignancies worldwide. More recently, the administration of immune checkpoint inhibitors has opened up more possibilities for cancer treatment.

Methods

We utilized a weighted gene co-expression network and the single sample gene set enrichment analysis (ssGSEA) algorithm in the TCGA database and identified a module highly correlated with regulatory T cell (Treg) abundance in OSCC. Subsequently, we verified the results by tissue microarrays and utilized immunohistochemical staining (IHC) to test the relationship between the expression level and clinicopathological staging. CCK-8, transwell, and wound healing assays were utilized to detect the functions of OSCC cells.

Results

LCK, IL10RA, and TNFRSF1B were selected as biomarkers related to regulatory T cell infiltration. IHC staining showed significantly increased expression of LCK, IL10RA or TNFRSF1B in OSCC patients, and the expression levels were associated with tumor stage, lymph node metastasis, pathological stage, clinical status and the overall survival. In vitro experiments showed that LCK, IL10RA or TNFRSF1B knockdown efficiently impaired the proliferative, migrative, and invasive capacity in OSCC cell lines.

Conclusion

We performed a series of bioinformatics analyses in OSCC and identified three oncogenic indicators: LCK, IL10RA, TNFRSF1B. These findings uncovered the potential prognostic values of hub genes, thus laying foundations for in-depth research in OSCC.

New horizons in drug discovery of lymphocyte-specific protein tyrosine kinase (Lck) inhibitors: a decade review (2011-2021) focussing on structure-activity relationship (SAR) and docking insights

Lymphocyte-specific protein tyrosine kinase (Lck), a non-receptor Src family kinase, has a vital role in various cellular processes such as cell cycle control, cell adhesion, motility, proliferation, and differentiation. Lck is reported as a key factor regulating the functions of T-cell including the initiation of TCR signalling, T-cell development, in addition to T-cell homeostasis. Alteration in expression and activity of Lck results in numerous disorders such as cancer, asthma, diabetes, rheumatoid arthritis, atherosclerosis, and neuronal diseases. Accordingly, Lck has emerged as a novel target against different diseases. Herein, we amass the research efforts in literature and pharmaceutical patents during the last decade to develop new Lck inhibitors. Additionally, structure-activity relationship studies (SAR) and docking models of these new inhibitors within the active site of Lck were demonstrated offering deep insights into their different binding modes in a step towards the identification of more potent, selective, and safe Lck inhibitors.

Parallel genome-wide RNAi screens identify lymphocyte-specific protein tyrosine kinase (LCK) as a targetable vulnerability of cell proliferation and chemoresistance in nasopharyngeal carcinoma

Despite recent in advances in the management of nasopharyngeal carcinoma (NPC), development of targeted therapy remains challenging particularly in patients with recurrent or metastatic disease. To search for clinically relevant targets for the treatment of NPC, we carried out parallel genome-wide functional screens to identified essential genes that are required for NPC cells proliferation and cisplatin resistance. We identified lymphocyte-specific protein tyrosine kinase (LCK) as a key vulnerability of both proliferation and cisplatin resistance. Depletion of endogenous LCK or treatment of cells with LCK inhibitor induced tumor-specific cell death and synergized cisplatin sensitivity in EBV-positive C666-1 and EBV-negative SUNE1 cells. Further analyses demonstrated that LCK is regulating the proliferation and cisplatin resistance through activation of signal transducer and activator of transcription 5 (STAT5). Taken together, our study provides a molecular basis for targeting LCK and STAT5 signaling as potential druggable targets for the management of NPC.

CXCL10 is a potential biomarker and associated with immune infiltration in human papillary thyroid cancer

Background: In recent years, the annual incidence of thyroid cancer (TC) has increased, with papillary thyroid cancer (PTC) identified as the most commonwinwordpathological type accounting for approximately 80% of all thyroid cancer cases. The tumor microenvironment is known to play a vital role in tumor information transmission and immune detection.

Methods: In the present study, we examined gene expression data from 518 patients with PTC. The ESTIMATE algorithm was used to calculate immune and stromal scores of PTC patients. Based on a protein–protein interaction (PPI) network, functional enrichment and overall survival analyses, C-X-C motif chemokine ligand 10 (CXCL10) was identified as a core gene. We further investigated the roles of core genes of PTC in the tumor immune microenvironment using LinkedOmics, GSEA, and TIMER tools.

Results: Immune, stromal and ESTIMATE scores were related to clinicopathological variables of patients with PTC, but not survival outcomes. Eight differentially expressed genes (DEGs) were associated with survival outcome. In addition, immunochemical staining experiments revealed lower expression of CXCL10 in PTC than paracancerous tissues. GSEA pathway enrichment analysis revealed downregulation of CXCL10 in multiple cancer pathways. CXCL10 and related genes were enriched in pathways related to adaptive immune response, cellular defense response and regulation of innate immune response.

Conclusion: The tumor microenvironment plays a critical role in development of PTC and CXCL10 may serve as a novel target of precision therapy for this patient population.

The mechanobiome: a goldmine for cancer therapeutics

Cancer progression is dependent on heightened mechanical adaptation, both for the cells' ability to change shape and to interact with varying mechanical environments. This type of adaptation is dependent on mechanoresponsive proteins that sense and respond to mechanical stress, as well as their regulators. Mechanoresponsive proteins are part of the mechanobiome, which is the larger network that constitutes the cell's mechanical systems that are also highly integrated with many other cellular systems, such as gene expression, metabolism, and signaling. Despite the altered expression patterns of key mechanobiome proteins across many different cancer types, pharmaceutical targeting of these proteins has been overlooked. Here, we review the biochemistry of key mechanoresponsive proteins, specifically nonmuscle myosin II, α-actinins, and filamins, as well as the partnering proteins 14-3-3 and CLP36. We also examined a wide range of data sets to assess how gene and protein expression levels of these proteins are altered across many different cancer types. Finally, we determined the potential of targeting these proteins to mitigate invasion or metastasis and suggest that the mechanobiome is a goldmine of opportunity for anticancer drug discovery and development.

Comprehensively investigating the expression levels and the prognostic role of transforming growth factor beta-induced (TGFBI) in glioblastoma multiforme

BACKGROUND

Transforming growth factor beta-induced (TGFBI) protein has been found expressed in several cancer types, and expression levels of TGFBI can affect the cancer patients' outcomes, but the role of TGFBI in glioblastoma multiforme (GBM) remains obscure.

METHODS

The TGFBI expression levels in GBM were performed via Gene Expression Profiling Interactive Analysis (GEPIA) and UALCAN databases. Further, the mutations types of TGFBI were analyzed by using the cBioportal dataset. LinkedOmics selected correlated genes, kinases, and microRNA (miRNA) targets of TGFBI. GEPIA conducted the prognostic value of TGFBI and correlated genes. Then, the relationship between TGFBI and immune infiltrates was performed by Tumor Immune Estimation Resource (Timer). We compared the TGFBI protein expression levels in GBM and control samples through the Human Protein Atlas (HPA). Finally, the GSCAlite was used to achieve the drugs, and molecules target the TGFBI and significantly correlated genes.

RESULTS

TGFBI is significantly overexpressed in GBM, but the clinical features do not have considerable influence on TGFBI expression levels. Overexpression of TGFBI acts as an adverse biomarker of GBM. The enrichment function of TGFBI showed that the main biological functions, including extracellular matrix (ECM) organization, angiogenesis, leukocyte migration, T cell activation, cell cycle G2/M phase transition, and growth factor binding. About the significant correlated genes, overexpression of mitogen-activated protein kinase 13 (MAPK13) [Log-rank P=0.08 HR (high) =1.4], myosin IG (MYO1G) [Log-rank P=0.06 HR (high) =1.4], plasminogen activator urokinase receptor (PLAUR) [Log-rank P=0.03 HR (high) =1.5], thrombomodulin (THBD) [Log-rank P=0.028 HR (high) =1.5] indicated the poor prognosis of GBM. Further, TGFBI had a significant association with dendritic cell (DC) infiltrates (cor =0.516, P=9.00e-30). The higher the DC infiltration, the shorter survival of GBM. TGFBI protein expression levels were not significantly different in GBM and normal tissue. Finally, TGFBI is associated with resistance to belinostat, LAQ824, CAY10603, CUDC-101, methotrexate, 5-fluorouracil, and navitoclax.

CONCLUSIONS

In the present study, we showed TGFBI was overexpressed in GBM, and TGFBI is associated with DC cell infiltrates. Overexpression of TGFBI and high DC infiltration might be an adverse biomarker of GBM. Finally, TGFBI is associated with tumor multi-drug resistance.

Ductal carcinoma in situ of breast: update 2019

Ductal carcinoma in situ is a non-invasive form of breast cancer. Its incidence is increasing due to widespread use of mammographic screening. It presents several diagnostic and management challenges in part due to its relatively indolent behaviour. Most series analysing biomarkers in these lesions are small (<100 patients) and large clinical trials have not been frequent. Herein, we review the recent progress made in understanding the biology of this entity and the tools available for prognostication.

Beyond TCR Signaling: Emerging Functions of Lck in Cancer and Immunotherapy

In recent years, the lymphocyte-specific protein tyrosine kinase (Lck) has emerged as one of the key molecules regulating T-cell functions. Studies using Lck knock-out mice or Lck-deficient T-cell lines have shown that Lck regulates the initiation of TCR signaling, T-cell development, and T-cell homeostasis. Because of the crucial role of Lck in T-cell responses, strategies have been employed to redirect Lck activity to improve the efficacy of chimeric antigen receptors (CARs) and to potentiate T-cell responses in cancer immunotherapy. In addition to the well-studied role of Lck in T cells, evidence has been accumulated suggesting that Lck is also expressed in the brain and in tumor cells, where it actively takes part in signaling processes regulating cellular functions like proliferation, survival and memory. Therefore, Lck has emerged as a novel druggable target molecule for the treatment of cancer and neuronal diseases. In this review, we will focus on these new functions of Lck.

Weighted gene co-expression network analysis reveals modules and hub genes associated with the development of breast cancer

This study aimed to identify modules associated with breast cancer (BC) development by constructing a gene co-expression network, and mining hub genes that may serve as markers of invasive breast cancer (IBC).We downloaded 2 gene expression datasets from the Gene Expression Omnibus (GEO) database, and used weighted gene co-expression network analysis (WGCNA) to dynamically study the changes of co-expression genes in normal breast tissues, ductal carcinoma in situ (DCIS) tissues, and IBC tissues. Modules that highly correlated with BC development were carried out functional enrichment analysis for annotation, visualization, and integration discovery. The hub genes detected by WGCNA were also confirmed using the Oncomine dataset.We detected 17 transcriptional modules in total and 4 - namely tan, greenyellow, turquoise, and brown - were highly correlated with BC development. The functions of these 4 modules mainly concerned cell migration (tan module, P = 3.03 × 10), the cell cycle (greenyellow module, P = 3.08 × 10), cell-cell adhesion (turquoise module, P = .002), and the extracellular exosome (brown module, P = 1.38 × 10). WGCNA also mined the hub genes, which were highly correlated with the genes in the same module and with BC development. The Oncomine database confirmed that the expressions levels of 6 hub genes were significantly higher in BC tissues than in normal tissues, with fold changes larger than 2 (all P < .05). Apart from the 2 well-known genes EPCAM and MELK, during the development of BC, KRT8, KRT19, KPNA2, and ECT2 also play key roles, and may be used as new targets for the detection or treatment of BC.In summary, our study demonstrated that hub genes such as EPCAM and MELK are highly correlated with breast cancer development. However, KRT8, KRT19, KPNA2, and ECT2 may also have potential as diagnostic and prognostic biomarkers of IBC.