Distinct patterns of angiogenic factor expression as a predictive factor of response to chemotherapy in stage IIIA non-small-cell lung cancer patients

Koufos, Nikolaos; Syrios, John; Michailidou, Despina; Xynos, Ioannis; Lazaris, Andreas C.; Kavantzas, N; Tomos, Periclis; Kakaris, Stamatios; Kosmas, Christos; Tsavaris, Nikolas

doi:10.3892/mco.2016.966

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…The prognostic and predictive value of HGF included in serum or plasma cytokine and angiogenic factor profile analysis has been explored in different tumor types [205,[228][229][230][231]. In a recent study, Saltarella et al evaluated the panel of angiogenic factors including HGF in multiple myeloma patients; they suggested that increased plasma HGF was associated with shorter relative PFS and predicted the benefit from therapeutic regimens [205].…”

Section: V-j-multiple Myelomamentioning

confidence: 99%

HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers

Moosavi

Giovannetti

Saso³

et al. 2019

Critical Reviews in Clinical Laboratory Sciences

129

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Cancer is a major cause of death worldwide. MET tyrosine kinase receptor [MET, c-MET, hepatocyte growth factor (HGF) receptor] pathway activation is associated with the appearance of several hallmarks of cancer. The HGF/MET pathway has emerged as an important actionable target across many solid tumors; therefore, biomarker discovery becomes essential in order to guide clinical intervention and patient stratification with the aim of moving towards personalized medicine. The focus of this review is on how the aberrant activation of the HGF/MET pathway in tumor tissue or the circulation can provide diagnostic and prognostic biomarkers and predictive biomarkers of drug response. Many meta-analyses have shown that aberrant activation of the MET pathway in tumor tissue, including MET gene overexpression, gene amplification, exon 14 skipping and other activating mutations, is almost invariably associated with shorter survival and poor prognosis. Most meta-analyses have been performed in non-small cell lung cancer (NSCLC), breast, head and neck cancers as well as colorectal, gastric, pancreatic and other gastrointestinal cancers. Furthermore, several studies have shown the predictive value of MET biomarkers in the identification of patients who gain the most benefit from HGF/MET targeted therapies administered as single or combination therapies. The highest predictive values have been observed for response to foretinib and savolitinib in renal cancer, as well as tivantinib in NSCLC and colorectal cancer. However, some studies, especially those based on MET expression, have failed to show much value in these stratifications. This may be rooted in lack of standardization of methodologies, in particular in scoring systems applied in immunohistochemistry determinations or absence of oncogenic addiction of cancer cells to the MET pathway, despite detection of overexpression. Measurements of amplification and mutation aberrations are less likely to suffer from these pitfalls. Increased levels of MET soluble ectodomain (sMET) in circulation have also been associated with poor prognosis; however, the evidence is not as strong as it is with tissue-based biomarkers. As a diagnostic biomarker, sMET has shown its value in distinguishing cancer patients from healthy individuals in prostate and bladder cancers and in melanoma. On the other hand, increased circulating HGF has also been presented as a valuable prognostic and diagnostic biomarker in many cancers; however, there is controversy on the predictive value of HGF as a biomarker. Other biomarkers such as circulating tumor DNA (ctDNA) and tumor HGF levels have also been briefly covered. In conclusion, HGF/MET aberrations can provide valuable diagnostic, prognostic and predictive biomarkers and represent vital assets for personalized cancer therapy.

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Section: V-j-multiple Myelomamentioning

confidence: 99%

HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers

Moosavi

Giovannetti

Saso³

et al. 2019

Critical Reviews in Clinical Laboratory Sciences

129

View full text Add to dashboard Cite

show abstract

“…As interventions, treatments, or environmental stimuli induce alterations in the transcriptome, the study of signature reversion [47] delves into the intriguing phenomenon of whether the gene expression profile returns to its original state over time [48]. This process is paramount in deciphering the long-term impacts of therapeutic interventions [49], guiding researchers to discern the resilience and adaptability of cellular responses. The investigation of transcriptome signature reversion holds immense significance, particularly in drug development and precision medicine.…”

Section: Gene Expression Signatures and Drug Repurposingmentioning

confidence: 99%

Genomic Approaches for Drug Repurposing

Dave,

Sharma,

Patel

et al. 2024

Preprint

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Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modelling of gene expression networks that involve large amounts of data. The integration of data from DNA, RNA, and protein activities has resemblance to pharmacogenomics, which is of utmost importance in the development of cancer drugs. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Expanding the study and application of functional genomics has great promise to advance the process of discovering and repurposing drugs, especially in the field of oncology.

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Genomic strategies for drug repurposing

Dave,

Patel,

Dave

et al. 2024

J Egypt Natl Canc Inst

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Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modeling of gene expression networks that involve large amounts of data. The amalgamation of data concerning DNA, RNA, and protein functions bears similarity to pharmacogenomics, a crucial aspect in crafting cancer therapeutics. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Broadening the exploration and utilization of functional genomics holds significant potential for advancing drug discovery and repurposing, particularly within the realm of oncology.

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Distinct patterns of angiogenic factor expression as a predictive factor of response to chemotherapy in stage IIIA non-small-cell lung cancer patients

Cited by 3 publications

References 41 publications

HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers

HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers

Genomic Approaches for Drug Repurposing

Genomic strategies for drug repurposing

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