The clinical significance of platelet-derived growth factors (PDGFs) and their receptors (PDGFRs) in gastric cancer: A systematic review and meta-analysis

The Role of Biomarkers in the Early Diagnosis of Gastric Cancer: A Study on CCR5, CCL5, PDGF, and EphA7

Despite the use of screening programs, gastric cancer (GC) diagnosis may only be possible at an advanced stage. In this study, we examined the serum levels of C-C chemokine receptor type 5 (CCR5), C-C motif chemokine ligand 5 (CCL5), platelet-derived growth factor (PDGF), and EphrinA7 (EphA7) in patients with gastric carcinoma and healthy controls to investigate the significance and usability of these potential biomarkers in the early diagnosis of GC. The study enrolled 69 GC patients and 40 healthy individuals. CCR5, CCL5, PDGF-BB, and EphA7 levels, which have been identified in the carcinogenesis of many cancers, were measured in the blood samples using the ELISA method. CCR5, CCL5, PDGF-BB, and EphA7 were all correlated with GC diagnosis (CCR5, p < 0.001, r = -0.449; CCL5, p = 0.014, r = -0.234; PDGF-BB, p < 0.001, r = -0.700; EPHA7, p < 0.001, r = -0.617). The serum CCR5, EphA7, and especially the PDGF-BB levels of the patients diagnosed with GC were discovered to be significantly higher compared to the healthy controls. PDGF-BB had the highest positive and negative predictive values when evaluated in ROC analysis to determine its diagnostic significance (cut-off value: 59.8 ng/L; AUC: 0.92 (0.87-0.97)). As far as we know, this is the first study to investigate the potential connection between GC and these four biomarkers. The fact that serum CCR5, CCL5, EphA7, and especially PDGF-BB levels in the patient group were significantly higher compared to healthy controls indicates that they can be used with high accuracy in the early diagnosis of GC. In addition, the levels of CCR5, PDGF-BB, and EphA7 can be used as important indicators to predict the biological behavior and prognosis of GC.

Therapeutic advances of targeting receptor tyrosine kinases in cancer

Receptor tyrosine kinases (RTKs), a category of transmembrane receptors, have gained significant clinical attention in oncology due to their central role in cancer pathogenesis. Genetic alterations, including mutations, amplifications, and overexpression of certain RTKs, are critical in creating environments conducive to tumor development. Following their discovery, extensive research has revealed how RTK dysregulation contributes to oncogenesis, with many cancer subtypes showing dependency on aberrant RTK signaling for their proliferation, survival and progression. These findings paved the way for targeted therapies that aim to inhibit crucial biological pathways in cancer. As a result, RTKs have emerged as primary targets in anticancer therapeutic development. Over the past two decades, this has led to the synthesis and clinical validation of numerous small molecule tyrosine kinase inhibitors (TKIs), now effectively utilized in treating various cancer types. In this manuscript we aim to provide a comprehensive understanding of the RTKs in the context of cancer. We explored the various alterations and overexpression of specific receptors across different malignancies, with special attention dedicated to the examination of current RTK inhibitors, highlighting their role as potential targeted therapies. By integrating the latest research findings and clinical evidence, we seek to elucidate the pivotal role of RTKs in cancer biology and the therapeutic efficacy of RTK inhibition with promising treatment outcomes.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Cross-talk between gastric cancer and hepatic stellate cells promotes invadopodia formation during liver metastasis

In gastric cancer (GC), the liver is a common organ for distant metastasis, and patients with gastric cancer with liver metastasis (GCLM) generally have poor prognosis. The mechanism of GCLM is unclear. Invadopodia are special membrane protrusions formed by tumor cells that can degrade the basement membrane and ECM. Herein, we investigated the role of invadopodia in GCLM. We found that the levels of invadopodia-associated proteins were significantly higher in liver metastasis than in the primary tumors of patients with GCLM. Furthermore, GC cells could activate hepatic stellate cells (HSCs) within the tumor microenvironment of liver metastases through the secretion of platelet-derived growth factor subunit B (PDGFB). Activated HSCs secreted hepatocyte growth factor (HGF), which activated the MET proto-oncogene, MET receptor of GC cells, thereby promoting invadopodia formation through the PI3K/AKT pathway and subsequently enhancing the invasion and metastasis of GC cells. Therefore, cross-talk between GC cells and HSCs by PDGFB/platelet derived growth factor receptor beta (PDGFRβ) and the HGF/MET axis might represent potential therapeutic targets to treat GCLM.

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer

Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics, transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances associated with various omics are concurrently altered during gastric cancer development. Furthermore, environmental exposures and family history can also induce modifications in endogenous substances. Therefore, in this study, we primarily investigated alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA, and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels in the context of GC development, employing genomics, transcriptomics, proteomics, and metabolomics. Additionally, we elucidate the impact of exposure factors, including HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and metabolomics; ii) the influence of environmental exposure and family history on multiomics data; iii) the integrated analysis of multi-omics data using machine learning techniques.

Systemic immune-inflammation index: A new marker in differentiation of different thyroid diseases

Inflammation plays an important role in the pathogenesis of many cancer types and is associated with thyroid malignancy. The systemic immune-inflammation index (SII) is a new inflammation marker that can be calculated from routine complete blood count (CBC). This study investigated the association between SII, a marker derived from routine CBC, and different thyroid diseases. The objective was to determine if this simple inflammation marker can distinguish between benign and malignant thyroid diseases. The medical records of all patients who underwent surgical treatment for thyroid disease between January 2018 and January 2022 were systematically evaluated. The routine preoperative CBC parameters' demographic, clinical, and laboratory data were recorded. A total of 241 patients were included in the study, and the patients were grouped as having multinodular goiter (n = 125), lymphocytic thyroiditis (n = 44), and papillary thyroid carcinoma (PTC) (n = 73) according to pathological results. The SII was defined as the ratio of the total count of neutrophils × platelets divided by the lymphocyte count. Subgroup analysis of patients was performed according to the presence of follicular variant or thyroiditis, micro or macro carcinoma, or bilaterality of the tumor. The SII level was significantly higher in the PTC group than in the lymphocytic thyroiditis and multinodular goiter groups (P < .001). When we grouped the patients according to the presence of PTC as benign or malignant, the optimum cutoff point for SII level was found 654.13, with 73.8% sensitivity and 72.3% specificity from ROC analysis. In the subgroup analysis of patients with PTC, the SII level was similar according to the clinicopathological characteristics of the tumor. The differential diagnosis of thyroid diseases is important for patient management. We found that preoperative SII levels were significantly elevated in patients with PTC compared to those with benign thyroid disorders, and this simple marker can be used for the differentiation of benign and malignant thyroid disease.

New insights about the PDGF/PDGFR signaling pathway as a promising target to develop cancer therapeutic strategies

Numerous cancers express platelet-derived growth factors (PDGFs) and PDGF receptors (PDGFRs). By directly stimulating tumour cells in an autocrine manner or by stimulating tumour stromal cells in a paracrine manner, the platelet-derived growth factor (PDGF)/platelet-derived growth factor receptor (PDGFR) pathway is crucial in the growth and spread of several cancers. To combat hypoxia in the tumour microenvironment, it encourages angiogenesis. A growing body of experimental data shows that PDGFs target malignant cells, vascular cells, and stromal cells to modulate tumour growth, metastasis, and the tumour microenvironment. To combat medication resistance and enhance patient outcomes in cancers, targeting the PDGF/PDGFR pathway is a viable therapeutic approach. There have been reports of anomalies in the PDGF pathway, including the gain of function point mutations, activating chromosomal translocations, or overexpression or amplification of PDGF receptors (PDGFRs). As a result, it has been shown that targeting the PDGF/PDGFR signaling pathway is an effective method for treating cancer. As a result, this study will concentrate on the regulation of the PDGF/PDGFR signaling system, in particular the current methods and inhibitors used in cancer treatment, as well as the associated therapeutic advantages and side effects.

Platelet-Derived Growth Factors Affect Clinical Features and Prognosis of Gastric Cancer

Purpose. To investigate the association of platelet-derived growth factors (PDGFs), clinicopathological features, and prognosis in gastric cancer patients. Methods. Tumor specimens of 180 individuals with gastric cancer treated between 2016 and 2020 were collected. Immunohistochemical staining and Western blot (WB) were used to detect the expression of PDGF-B and PDGF-D. The relationship between the expression of PDGF-B and PDGF-D and relapse-free subsistence (RFS) time was assessed using Kaplan–Meier curves. Univariate and multivariate Cox proportional hazards regression models were used to evaluate the relationship between the expression of PDGF-B and PDGF-D and the prognosis and clinicopathological features in gastric cancer patients. Results. High expression of PDGF-B and PDGF-D was detected in 108 (60%) and 137 (76%) tumor specimens, respectively. The expressions of PDGF-B and PDGF-D were independent predictive indicators in multivariate analysis when compared to tumor depth, tumor stage, lymph node metastasis, and RFS ( $P<0.01$ ). Conclusion. The high expression of PDGF-B and PDGF-D in gastric cancer tissues is associated with poor prognosis and poor survival rate of the patients. The expression of PDGF-B and PDGF-D can be used as important indicators to evaluate the biological behavior and prognosis of gastric cancer.

Downregulation of PDGF-D Inhibits Proliferation and Invasion in Breast Cancer MDA-MB-231 Cells

BACKGROUND

The platelet derived growth factor-D (PDGF-D) plays an important role in breast tumor aggressiveness. However, limited study has investigated the effect of silencing PDGF-D on the biological function of breast cancer. The purpose of this study is to clarify the potential value of PDGF-D as a target for breast cancer treatment.

METHODS

Reverse transcription-polymerase chain reaction and western blot were used to detect PDGF-D expression in 5 different breast cancer cells. The lentiviral vector was usd to silence PDGF-D in MDA-MB-231 cells. Then, Methyl Thiazolyl Tetrazolium was used to detect cell viability, 5-Ethynyl-2'- deoxyuridine and a soft agar assay were used to detect cell proliferation and clonality. Additionally, cell apoptosis after PDGF-D knockdown was measured by Annexin V/ Prodium Iodide staining, and cell migration was detected by trans-well assay. Survival rate and tumor size were measured by nude mice transplantation.

RESULTS

The MDA-MB-231 and SK-BR-3 cell lines showed higher PDGF-D expression than the MCF7 cell lines (P<.05). After the PDGF-D gene was silenced, the growth and colony forming abilitys ignificantly decreased (P<.05) together with the induction of apoptosis in MDA-MB-231 cells (P<.05). Moreover, MDA-MB-231 cells with PDGF-D silencing showed significantly diminished aggressive migration and invasion potential compared to other cells (P<.05). In vivo experiments also indicated that PDGF-D silencing inhibited tumor growth and improved the survival rate of tumor-bearing mice.

CONCLUSION

Downregulation of PDGF-D had dramatic effects on breast cancer cell proliferation, apoptosis and migration, which indicates that it plays an important role in breast cancer development and progression.

Construction and Validation of a Universal Applicable Prognostic Signature for Gastric Cancer Based on Seven Immune-Related Gene Correlated With Tumor Associated Macrophages

Background

Tumor-associated macrophages (TAMs) play a critical role in the progression of malignant tumors, but the detailed mechanism of TAMs in gastric cancer (GC) is still not fully explored.

Methods

We identified differentially expressed immune-related genes (DEIRGs) between GC samples with high and low macrophage infiltration in The Cancer Genome Atlas datasets. A risk score was constructed based on univariate Cox analysis and Lasso penalized Cox regression analysis in the TCGA cohort (n=341). The optimal cutoff determined by the 5-year time-dependent receiver operating characteristic (ROC) curve was considered to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE84437, n=431; GSE62254, n=300; GSE15459, n=191; and GSE26901, n=109) from the Gene Expression Omnibus (GEO) database.

Results

The signature consisting of 7 genes (FGF1, GRP, AVPR1A, APOD, PDGFRL, CXCR4, and CSF1R) showed good performance in predicting overall survival (OS) in the 5 independent cohorts. The risk score presented an obviously positive correlation with macrophage abundance (cor=0.7, p<0.001). A significant difference was found between the high- and low-risk groups regarding the overall survival of GC patients. The high-risk group exhibited a higher infiltration level of M2 macrophages estimated by the CIBERSORT algorithm. In the five independent cohorts, the risk score was highly positively correlated with the stromal cell score, suggesting that we can also evaluate the infiltration of stromal cells in the tumor microenvironment according to the risk score.

Conclusion

Our study developed and validated a general applicable prognostic model for GC from the perspective of TAMs, which may help to improve the precise treatment strategy of GC.

The systemic immune-inflammation index-based model is an effective biomarker on predicting central lymph node metastasis in clinically nodal-negative papillary thyroid carcinoma

Background

A high proportion of papillary thyroid carcinoma (PTC) patients are involved in central lymph node metastasis (CLNM) with preoperative imaging examinations showing clinically nodal-negative (cN0). Meanwhile, many inflammatory biomarkers are also proven as effective factors to predict the outcomes of cancer patients and tumor progression. Thus, the values of these factors are investigated to help detecting CLNM in cN0 PTC patients.

Methods

406 cN0 PTC patients who underwent curative surgery were retrospectively analyzed. CLNM was determined by histopathological examination following the thyroidectomy. Multiple inflammatory biomarkers were comprehensively researched.

Results

A total of 406 consecutive patients were eventually included. The univariate and multivariate analyses revealed that age (OR: 0.924, 95% CI: 0.909, 0.940), gender (OR: 1.781, 95% CI: 1.060, 2.993), location of tumors (OR: 2.229, 95% CI: 1.228, 4.046) and level of systemic immune-inflammation index (SII) (OR: 1.005, 95% CI: 1.004, 1.006) were independently associated with CLNM in cN0 PTC patients, and the SII-based predictive model was constructed using these four factors. Receiver operating characteristic (ROC) curves showed significant results of the SII-based predictive model in PTC cohort with area under curve (AUC) as 0.814 (95% CI: 0.771-0.857) and in PTMC subgroup with AUC as 0.803 (95% CI: 0.752-0.854).

Conclusions

The SII-based model can effectively help predicting CLNM in both cN0 PTC patients and cN0 PTMC patients.

Role of Extracellular Matrix in Gastrointestinal Cancer-Associated Angiogenesis

Gastrointestinal tumors are responsible for more cancer-related fatalities than any other type of tumors, and colorectal and gastric malignancies account for a large part of these diseases. Thus, there is an urgent need to develop new therapeutic approaches to improve the patients' outcome and the tumor microenvironment is a promising arena for the development of such treatments. In fact, the nature of the microenvironment in the different gastrointestinal tracts may significantly influence not only tumor development but also the therapy response. In particular, an important microenvironmental component and a potential therapeutic target is the vasculature. In this context, the extracellular matrix is a key component exerting an active effect in all the hallmarks of cancer, including angiogenesis. Here, we summarized the current knowledge on the role of extracellular matrix in affecting endothelial cell function and intratumoral vascularization in the context of colorectal and gastric cancer. The extracellular matrix acts both directly on endothelial cells and indirectly through its remodeling and the consequent release of growth factors. We envision that a deeper understanding of the role of extracellular matrix and of its remodeling during cancer progression is of chief importance for the development of new, more efficacious, targeted therapies.

Haematological adverse events associated with tyrosine kinase inhibitors in chronic myeloid leukaemia: A network meta-analysis

AIMS

Despite their overall favourable safety profile, tyrosine kinase inhibitors (TKIs) are related to severe adverse events including haematological toxicities such as anaemia, leucopenia, neutropenia and thrombocytopenia. We designed a systematic review and network meta-analysis of randomised controlled trials to compare safety among TKIs (bosutinib, dasatinib, imatinib, nilotinib, ponatinib and radotinib) used by patients diagnosed with chronic myeloid leukaemia.

METHODS

We obtained data from the PubMed, Scopus, Web of Science, and SciELO databases. The Bayesian approach was used for direct and indirect comparisons, and the treatments were ranked by the surface under the cumulative ranking curve (SUCRA).

RESULTS

Seventeen studies were included in the network meta-analysis. Our data show that dasatinib was generally considered worse than the other TKIs, with SUCRA values ​​for 140 mg dasatinib of 90.3% for anaemia, 87.4% for leucopenia, 90.6% for neutropenia and 97.2% for thrombocytopenia. In addition, nilotinib was shown to be safer, with SUCRA values ​​for 600 and 800 mg doses of 21.9 and 35.8% for anaemia, 23.8 and 14.6% for leucopenia, 33.0 and 17.7% for neutropenia, and 28.7 and 32.6% for thrombocytopenia, respectively.

CONCLUSION

Dasatinib appeared as the least safe drug for chronic myeloid leukaemia, probably because it binds to multiple key kinase targets, being more prone to cause serious haematological adverse events. Nilotinib demonstrated a safer profile, mostly due to its selective binding capacity.

Targeting Tyrosine kinases in Renal Cell Carcinoma: "New Bullets against Old Guys"

Clear cell renal cell carcinoma (ccRCC) is the seventh most frequently diagnosed tumor in adults in Europe and represents approximately 2.5% of cancer deaths. The molecular biology underlying renal cell carcinoma (RCC) development and progression has been a key milestone in the management of this type of tumor. The discovery of Von Hippel Lindau (VHL) gene alterations that arouse in 50% of ccRCC patients, leads the identification of an intracellular accumulation of HIF and, consequently an increase of VEGFR expression. This change in cell biology represents a new paradigm in the treatment of metastatic renal cancer by targeting angiogenesis. Currently, there are multiple therapeutic drugs available for advanced disease, including therapies against VEGFR with successful results in patients´ survival. Other tyrosine kinases' pathways, including PDGFR, Axl or MET have emerged as key signaling pathways involved in RCC biology. Indeed, promising new drugs targeting those tyrosine kinases have exhibited outstanding efficacy. In this review we aim to present an overview of the central role of these tyrosine kinases' activities in relevant biological processes for kidney cancer and their usefulness in RCC targeted therapy development. In the immunotherapy era, angiogenesis is still an "old guy" that the medical community is trying to fight using "new bullets".

Risk of second primary tumors in GIST survivors: A systematic review and meta-analysis

INTRODUCTION

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal tumors arising in the gastrointestinal tract. Second primary tumors (SPTs) have been reported frequently, either synchronously or during follow-up, in patients diagnosed with GISTs.

METHODS

We carried out an electronic search of PubMed, SCOPUS, Web of Science, EMBASE, and the Cochrane Library seeking articles investigating the incidence of SPTs in patients with concomitant GIST. All studies were evaluated for heterogeneity before meta-analysis and for publication bias. Pooled incidence rate was estimated using fixed- and random-effects models. Subsite of SPTs was also investigated.

RESULTS

A total of 32 studies met the inclusion criteria, for a total of 19,627 patients with a diagnosis of GIST. The pooled prevalence of SPTs was 20%, with 14% and 3% being synchronous and metachronous tumors, respectively. We found a risk for several specific cancer sites, in particular gastrointestinal (5%) and genitourinary tract cancers (3%). The most frequently associated malignancies were: colorectal (17%), prostate (14%), gastric (9%), esophageal (5.5%), lung (5.4%), hepato-biliopancreatic (4.7%), breast (4.6%), lymphoma (4.4%), kidney (4.35%), and sarcomas (3.3%). Regression analyses revealed a significant positive association for all SPTs with follow-up and Miettinen risk.

CONCLUSIONS

Our results indicate that 20% of patients with GIST experienced a SPT, primarily synchronously with a diagnosis of GIST. In particular, we observed an excess of incident gastrointestinal tumors. These findings have important implications for both pathologists, who should perform extensive molecular analysis of surgical non-GIST specimens in resected patients, and for oncologists, who should continue to follow up GIST patients.

β-Arrestin Based Receptor Signaling Paradigms: Potential Therapeutic Targets for Complex Age-Related Disorders

G protein coupled receptors (GPCRs) were first characterized as signal transducers that elicit downstream effects through modulation of guanine (G) nucleotide-binding proteins. The pharmacotherapeutic exploitation of this signaling paradigm has created a drug-based field covering nearly 50% of the current pharmacopeia. Since the groundbreaking discoveries of the late 1990s to the present day, it is now clear however that GPCRs can also generate productive signaling cascades through the modulation of β-arrestin functionality. β-Arrestins were first thought to only regulate receptor desensitization and internalization - exemplified by the action of visual arrestin with respect to rhodopsin desensitization. Nearly 20 years ago, it was found that rather than controlling GPCR signal termination, productive β-arrestin dependent GPCR signaling paradigms were highly dependent on multi-protein complex formation and generated long-lasting cellular effects, in contrast to G protein signaling which is transient and functions through soluble second messenger systems. β-Arrestin signaling was then first shown to activate mitogen activated protein kinase signaling in a G protein-independent manner and eventually initiate protein transcription - thus controlling expression patterns of downstream proteins. While the possibility of developing β-arrestin biased or functionally selective ligands is now being investigated, no additional research has been performed on its possible contextual specificity in treating age-related disorders. The ability of β-arrestin-dependent signaling to control complex and multidimensional protein expression patterns makes this therapeutic strategy feasible, as treating complex age-related disorders will likely require therapeutics that can exert network-level efficacy profiles. It is our understanding that therapeutically targeting G protein-independent effectors such as β-arrestin will aid in the development of precision medicines with tailored efficacy profiles for disease/age-specific contextualities.