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19 pages, 4206 KiB

Open AccessArticle

Generation and Next-Generation Sequencing-Based Characterization of a Large Human Combinatorial Antibody Library

by Hye Lim Choi, Ha Rim Yang, Ha Gyeong Shin, Kyusang Hwang, Ji Woong Kim, Ji Hyun Lee, Taehoon Ryu, Yushin Jung and Sukmook Lee

Int. J. Mol. Sci. 2023, 24(6), 6011; https://doi.org/10.3390/ijms24066011 - 22 Mar 2023

Cited by 2 | Viewed by 2705

Abstract

Antibody phage display is a key technology for the discovery and development of target-specific monoclonal antibodies (mAbs) for use in research, diagnostics, and therapy. The construction of a high-quality antibody library, with larger and more diverse antibody repertoires, is essential for the successful [...] Read more.

Antibody phage display is a key technology for the discovery and development of target-specific monoclonal antibodies (mAbs) for use in research, diagnostics, and therapy. The construction of a high-quality antibody library, with larger and more diverse antibody repertoires, is essential for the successful development of phage display-derived mAbs. In this study, a large human combinatorial single-chain variable fragment library (1.5 × 10¹¹ colonies) was constructed from Epstein–Barr virus-infected human peripheral blood mononuclear cells stimulated with a combination of two of the activators of human B cells, the Toll-like receptor 7/8 agonist R848 and interleukin-2. Next-generation sequencing analysis with approximately 1.9 × 10⁶ and 2.7 × 10⁶ full-length sequences of heavy chain variable (VH) and κ light chain variable (Vκ) domains, respectively, revealed that the library consists of unique VH (approximately 94%) and Vκ (approximately 91%) sequences with greater diversity than germline sequences. Lastly, multiple unique mAbs with high affinity and broad cross-species reactivity could be isolated from the library against two therapeutically relevant target antigens, validating the library quality. These findings suggest that the novel antibody library we have developed may be useful for the rapid development of target-specific phage display-derived recombinant human mAbs for use in therapeutic and diagnostic applications. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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16 pages, 7096 KiB

Open AccessArticle

omicsGAT: Graph Attention Network for Cancer Subtype Analyses

by Sudipto Baul, Khandakar Tanvir Ahmed, Joseph Filipek and Wei Zhang

Int. J. Mol. Sci. 2022, 23(18), 10220; https://doi.org/10.3390/ijms231810220 - 06 Sep 2022

Cited by 3 | Viewed by 2493

Abstract

The use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer [...] Read more.

The use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer mechanisms compared to traditional approaches. Graph-based learning models have been proposed to learn important hidden representations from gene expression data and network structure to improve cancer outcome prediction, patient stratification, and cell clustering. However, these graph-based methods cannot rank the importance of the different neighbors for a particular sample in the downstream cancer subtype analyses. In this study, we introduce omicsGAT, a graph attention network (GAT) model to integrate graph-based learning with an attention mechanism for RNA-seq data analysis. The multi-head attention mechanism in omicsGAT can more effectively secure information of a particular sample by assigning different attention coefficients to its neighbors. Comprehensive experiments on The Cancer Genome Atlas (TCGA) breast cancer and bladder cancer bulk RNA-seq data and two single-cell RNA-seq datasets validate that (1) the proposed model can effectively integrate neighborhood information of a sample and learn an embedding vector to improve disease phenotype prediction, cancer patient stratification, and cell clustering of the sample and (2) the attention matrix generated from the multi-head attention coefficients provides more useful information compared to the sample correlation-based adjacency matrix. From the results, we can conclude that some neighbors play a more important role than others in cancer subtype analyses of a particular sample based on the attention coefficient. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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26 pages, 4822 KiB

Open AccessArticle

Gene Expression Landscape of Chronic Myeloid Leukemia K562 Cells Overexpressing the Tumor Suppressor Gene PTPRG

by Giulia Lombardi, Roberta Valeria Latorre, Alessandro Mosca, Diego Calvanese, Luisa Tomasello, Christian Boni, Manuela Ferracin, Massimo Negrini, Nader Al Dewik, Mohamed Yassin, Mohamed A. Ismail, Bruno Carpentieri, Claudio Sorio and Paola Lecca

Int. J. Mol. Sci. 2022, 23(17), 9899; https://doi.org/10.3390/ijms23179899 - 31 Aug 2022

Cited by 5 | Viewed by 2280

Abstract

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, [...] Read more.

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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26 pages, 54714 KiB

Open AccessArticle

Prostate Cancer Secretome and Membrane Proteome from Pten Conditional Knockout Mice Identify Potential Biomarkers for Disease Progression

by Nilton J. Santos, Ana Carolina Lima Camargo, Hernandes F. Carvalho, Luis Antonio Justulin and Sérgio Luis Felisbino

Int. J. Mol. Sci. 2022, 23(16), 9224; https://doi.org/10.3390/ijms23169224 - 17 Aug 2022

Cited by 3 | Viewed by 2245

Abstract

Prostate cancer (PCa) is the second most common cause of mortality among men. Tumor secretome is a promising strategy for understanding the biology of tumor cells and providing markers for disease progression and patient outcomes. Here, transcriptomic-based secretome analysis was performed on the [...] Read more.

Prostate cancer (PCa) is the second most common cause of mortality among men. Tumor secretome is a promising strategy for understanding the biology of tumor cells and providing markers for disease progression and patient outcomes. Here, transcriptomic-based secretome analysis was performed on the PCa tumor transcriptome of Genetically Engineered Mouse Model (GEMM) Pb-Cre4/Pten^f/f mice to identify potentially secreted and membrane proteins—PSPs and PMPs. We combined a selection of transcripts from the GSE 94574 dataset and a list of protein-coding genes of the secretome and membrane proteome datasets using the Human Protein Atlas Secretome. Notably, nine deregulated PMPs and PSPs were identified in PCa (DMPK, PLN, KCNQ5, KCNQ4, MYOC, WIF1, BMP7, F3, and MUC1). We verified the gene expression patterns of Differentially Expressed Genes (DEGs) in normal and tumoral human samples using the GEPIA tool. DMPK, KCNQ4, and WIF1 targets were downregulated in PCa samples and in the GSE dataset. A significant association between shorter survival and KCNQ4, PLN, WIF1, and F3 expression was detected in the MSKCC dataset. We further identified six validated miRNAs (mmu-miR-6962-3p, mmu-miR- 6989-3p, mmu-miR-6998-3p, mmu-miR-5627-5p, mmu-miR-15a-3p, and mmu-miR-6922-3p) interactions that target MYOC, KCNQ5, MUC1, and F3. We have characterized the PCa secretome and membrane proteome and have spotted new dysregulated target candidates in PCa. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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26 pages, 8439 KiB

Open AccessArticle

Survivin Inhibition by Piperine Sensitizes Glioblastoma Cancer Stem Cells and Leads to Better Drug Response

by Neerada Meenakshi Warrier, Ramesh Kumar Krishnan, Vijendra Prabhu, Raghu Chandrashekhar Hariharapura, Prasoon Agarwal and Praveen Kumar

Int. J. Mol. Sci. 2022, 23(14), 7604; https://doi.org/10.3390/ijms23147604 - 09 Jul 2022

Cited by 4 | Viewed by 2134

Abstract

Glioblastoma multiforme (GBM) cancer stem cells (GSCs) are one of the strongest contributing factors to treatment resistance in GBM. Identification of biomarkers capable of directly affecting these cells within the bulk tumor is a major challenge associated with the development of new targeting [...] Read more.

Glioblastoma multiforme (GBM) cancer stem cells (GSCs) are one of the strongest contributing factors to treatment resistance in GBM. Identification of biomarkers capable of directly affecting these cells within the bulk tumor is a major challenge associated with the development of new targeting strategies. In this study, we focus on understanding the potential of the multifunctional extraordinaire survivin as a biomarker for GSCs. We analyzed the expression profiles of this gene using various publicly available datasets to understand its importance in stemness and other cancer processes. The findings from these studies were further validated using human GSCs isolated from a GBM cell line. In these GSCs, survivin was inhibited using the dietary phytochemical piperine (PIP) and the subsequent effects on stemness, cancer processes and Temozolomide were investigated. In silico analysis identified survivin to be one of the most significant differentially regulated gene in GSCs, in comparison to common stemness markers. Further validation studies on the isolated GSCs showed the importance of survivin in stemness, cancer progression and therapy resistance. Taken together, our study identifies survivin as a more consistent GSC marker and also suggests the possibility of using survivin inhibitors along with standard of care drugs for better therapeutic outcomes. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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14 pages, 2921 KiB

Open AccessArticle

A Fully-Human Antibody Specifically Targeting a Membrane-Bound Fragment of CADM1 Potentiates the T Cell-Mediated Death of Human Small-Cell Lung Cancer Cells

by Ji Hyun Lee, Ji Woong Kim, Ha Rim Yang, Seong-Won Song, Song-Jae Lee, Yeongha Jeon, Anna Ju, Narim Lee, Min-Gu Kim, Minjoo Kim, Kyusang Hwang, Jin Hwan Yoon, Hyunbo Shim and Sukmook Lee

Int. J. Mol. Sci. 2022, 23(13), 6895; https://doi.org/10.3390/ijms23136895 - 21 Jun 2022

Cited by 4 | Viewed by 2539

Abstract

Small-cell lung cancer (SCLC) is the most aggressive form of lung cancer and the leading cause of global cancer-related mortality. Despite the earlier identification of membrane-proximal cleavage of cell adhesion molecule 1 (CADM1) in cancers, the role of the membrane-bound fragment of CAMD1 [...] Read more.

Small-cell lung cancer (SCLC) is the most aggressive form of lung cancer and the leading cause of global cancer-related mortality. Despite the earlier identification of membrane-proximal cleavage of cell adhesion molecule 1 (CADM1) in cancers, the role of the membrane-bound fragment of CAMD1 (MF-CADM1) is yet to be clearly identified. In this study, we first isolated MF-CADM1-specific fully human single-chain variable fragments (scFvs) from the human synthetic scFv antibody library using the phage display technology. Following the selected scFv conversion to human immunoglobulin G1 (IgG1) scFv-Fc antibodies (K103.1–4), multiple characterization studies, including antibody cross-species reactivity, purity, production yield, and binding affinity, were verified. Finally, via intensive in vitro efficacy and toxicity evaluation studies, we identified K103.3 as a lead antibody that potently promotes the death of human SCLC cell lines, including NCI-H69, NCI-H146, and NCI-H187, by activated Jurkat T cells without severe endothelial toxicity. Taken together, these findings suggest that antibody-based targeting of MF-CADM1 may be an effective strategy to potentiate T cell-mediated SCLC death, and MF-CADM1 may be a novel potential therapeutic target in SCLC for antibody therapy. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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16 pages, 5941 KiB

Open AccessArticle

EZH2–CCF–cGAS Axis Promotes Breast Cancer Metastasis

by Dandan Duan, Mengjie Shang, Yanxu Han, Jiayuan Liu, Jiwei Liu, Sun Hyok Kong, Jingyao Hou, Baiqu Huang, Jun Lu and Yu Zhang

Int. J. Mol. Sci. 2022, 23(3), 1788; https://doi.org/10.3390/ijms23031788 - 04 Feb 2022

Cited by 13 | Viewed by 3579

Abstract

Cytoplasmic chromatin fragments (CCF) are recognized by the cytoplasmic DNA sensor cyclic GMP-AMP synthase (cGAS), which activates the cGAS–STING (cyclic GMP-AMP synthase-stimulator of interferon genes) pathway and promotes the production of inflammatory factors and breast cancer metastasis. However, the mechanisms by which CCF [...] Read more.

Cytoplasmic chromatin fragments (CCF) are recognized by the cytoplasmic DNA sensor cyclic GMP-AMP synthase (cGAS), which activates the cGAS–STING (cyclic GMP-AMP synthase-stimulator of interferon genes) pathway and promotes the production of inflammatory factors and breast cancer metastasis. However, the mechanisms by which CCF are formed in tumor cells and CCF activation cGAS promotes breast cancer metastasis remain unclear. Here, we report that the enhancer of zeste homolog 2 (EZH2) can promote the formation of CCF and activate the cGAS–STING pathway to promote breast cancer metastasis. Further research found that the EZH2-mediated CCF formation depended on high mobility group A1 (HMGA1), while the stability of EZH2 required ubiquitin-specific peptidase 7 (USP7), indicating that the EZH2–HMGA1–USP7 complex regulated CCF formation. Moreover, EZH2 can activate cGAS through CCF, requiring USP7 to deubiquitinate cGAS and stabilize cGAS. In vivo experimental results showed that EZH2 could promote breast cancer metastasis through CCF. Our findings highlight a new target for breast cancer metastasis. Targeting the EZH2–CCF–cGAS axis may be a potential therapeutic strategy for inhibiting breast cancer metastasis. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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17 pages, 3326 KiB

Open AccessArticle

Effects of Anti-Cancer Drug Sensitivity-Related Genetic Differences on Therapeutic Approaches in Refractory Papillary Thyroid Cancer

by Hyeok Jun Yun, Minki Kim, Sang Yong Kim, Sungsoon Fang, Yonjung Kim, Hang-Seok Chang, Ho-Jin Chang and Ki Cheong Park

Int. J. Mol. Sci. 2022, 23(2), 699; https://doi.org/10.3390/ijms23020699 - 09 Jan 2022

Cited by 5 | Viewed by 2124

Abstract

Thyroid cancer (TC) includes tumors of follicular cells; it ranges from well differentiated TC (WDTC) with generally favorable prognosis to clinically aggressive poorly differentiated TC (PDTC) and undifferentiated TC (UTC). Papillary thyroid cancer (PTC) is a WDTC and the most common type of [...] Read more.

Thyroid cancer (TC) includes tumors of follicular cells; it ranges from well differentiated TC (WDTC) with generally favorable prognosis to clinically aggressive poorly differentiated TC (PDTC) and undifferentiated TC (UTC). Papillary thyroid cancer (PTC) is a WDTC and the most common type of thyroid cancer that comprises almost 70–80% of all TC. PTC can present as a solid, cystic, or uneven mass that originates from normal thyroid tissue. Prognosis of PTC is excellent, with an overall 10-year survival rate >90%. However, more than 30% of patients with PTC advance to recurrence or metastasis despite anti-cancer therapy; consequently, systemic therapy is limited, which necessitates expansion of improved clinical approaches. We strived to elucidate genetic distinctions due to patient-derived anti-cancer drug-sensitive or -resistant PTC, which can support in progress novel therapies. Patients with histologically proven PTC were evaluated. PTC cells were gained from drug-sensitive and -resistant patients and were compared using mRNA-Seq. We aimed to assess the in vitro and in vivo synergistic anti-cancer effects of a novel combination therapy in patient-derived refractory PTC. This combination therapy acts synergistically to promote tumor suppression compared with either agent alone. Therefore, genetically altered combination therapy might be a novel therapeutic approach for refractory PTC. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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Review

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25 pages, 1794 KiB

Open AccessReview

Influence of the Microbiome Metagenomics and Epigenomics on Gastric Cancer

by Precious Mathebela, Botle Precious Damane, Thanyani Victor Mulaudzi, Zilungile Lynette Mkhize-Khwitshana, Guy Roger Gaudji and Zodwa Dlamini

Int. J. Mol. Sci. 2022, 23(22), 13750; https://doi.org/10.3390/ijms232213750 - 09 Nov 2022

Cited by 1 | Viewed by 3047

Abstract

Gastric cancer (GC) is one of the major causes of cancer deaths worldwide. The disease is seldomly detected early and this limits treatment options. Because of its heterogeneous and complex nature, the disease remains poorly understood. The literature supports the contribution of the [...] Read more.

Gastric cancer (GC) is one of the major causes of cancer deaths worldwide. The disease is seldomly detected early and this limits treatment options. Because of its heterogeneous and complex nature, the disease remains poorly understood. The literature supports the contribution of the gut microbiome in the carcinogenesis and chemoresistance of GC. Drug resistance is the major challenge in GC therapy, occurring as a result of rewired metabolism. Metabolic rewiring stems from recurring genetic and epigenetic factors affecting cell development. The gut microbiome consists of pathogens such as H. pylori, which can foster both epigenetic alterations and mutagenesis on the host genome. Most of the bacteria implicated in GC development are Gram-negative, which makes it challenging to eradicate the disease. Gram-negative bacterium co-infections with viruses such as EBV are known as risk factors for GC. In this review, we discuss the role of microbiome-induced GC carcinogenesis. The disease risk factors associated with the presence of microorganisms and microbial dysbiosis are also discussed. In doing so, we aim to emphasize the critical role of the microbiome on cancer pathological phenotypes, and how microbiomics could serve as a potential breakthrough in determining effective GC therapeutic targets. Additionally, consideration of microbial dysbiosis in the GC classification system might aid in diagnosis and treatment decision-making, taking the specific pathogen/s involved into account. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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22 pages, 801 KiB

Open AccessReview

Drug Metabolism for the Identification of Clinical Biomarkers in Breast Cancer

by Bárbara Costa and Nuno Vale

Int. J. Mol. Sci. 2022, 23(6), 3181; https://doi.org/10.3390/ijms23063181 - 16 Mar 2022

Cited by 4 | Viewed by 3264

Abstract

Breast cancer is classified into four major molecular subtypes, and is considered a heterogenous disease. The risk profiles and treatment of breast cancer differ according to these subtypes. Early detection dramatically improves the prospects of successful treatment, resulting in a reduction in overall [...] Read more.

Breast cancer is classified into four major molecular subtypes, and is considered a heterogenous disease. The risk profiles and treatment of breast cancer differ according to these subtypes. Early detection dramatically improves the prospects of successful treatment, resulting in a reduction in overall mortality rates. However, almost 30% of women primarily diagnosed with the early-stage disease will eventually develop metastasis or resistance to chemotherapies. Immunotherapies are among the most promising cancer treatment options; however, long-term clinical benefit has only been observed in a small subset of responding patients. The current strategies for diagnosis and treatment rely heavily on histopathological examination and molecular diagnosis, disregarding the tumor microenvironment and microbiome involving cancer cells. In this review, we aim to praise the use of pharmacogenomics and pharmacomicrobiomics as a strategy to identify potential biomarkers for guiding and monitoring therapy in real-time. The finding of these biomarkers can be performed by studying the metabolism of drugs, more specifically, immunometabolism, and its relationship with the microbiome, without neglecting the information provided by genetics. A larger understanding of cancer biology has the potential to improve patient care, enable clinical decisions, and deliver personalized medicine. Full article

(This article belongs to the Special Issue From Omics to Therapeutic Targets in Cancer)

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