Multi-omics analysis to screen potential therapeutic biomarkers for anti-cancer compounds

Li, Ruxue; Zhou, Wuai

doi:10.1016/j.heliyon.2022.e09616

Cited by 5 publications

(3 citation statements)

References 52 publications

(53 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Liquid biopsies offer a non-invasive and real-time approach for detecting cancer-specific alterations, monitoring treatment response, and detecting minimal residual disease or cancer recurrence. , Integrating multiple omics data, including genomics, transcriptomics, proteomics, and metabolomics, can provide a more comprehensive understanding of cancer biology and help identify novel biomarkers. Analyzing multiple layers of molecular information can enhance diagnostic accuracy and predictive capabilities. − The application of artificial intelligence (AI) and machine learning (ML) algorithms can aid in the analysis and interpretation of complex biomarker data. AI can assist in identifying patterns, predicting disease outcomes, and improving the accuracy and efficiency of cancer diagnosis. − MicroRNAs (miRNAs) and other non-coding RNAs (ncRNAs) have shown promise as potential biomarkers due to their involvement in gene regulation and their dysregulation in various cancers.…”

Section: Outlook Challenges and Perspectivesmentioning

confidence: 99%

“…Integrating multiple omics data, including genomics, transcriptomics, proteomics, and metabolomics, can provide a more comprehensive understanding of cancer biology and help identify novel biomarkers. Analyzing multiple layers of molecular information can enhance diagnostic accuracy and predictive capabilities. − …”

Section: Outlook Challenges and Perspectivesmentioning

confidence: 99%

See 1 more Smart Citation

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Tenchov,

Sapra,

Sasso

et al. 2024

ACS Pharmacol. Transl. Sci.

View full text Add to dashboard Cite

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

show abstract

Section: Outlook Challenges and Perspectivesmentioning

confidence: 99%

Section: Outlook Challenges and Perspectivesmentioning

confidence: 99%

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Tenchov,

Sapra,

Sasso

et al. 2024

ACS Pharmacol. Transl. Sci.

View full text Add to dashboard Cite

show abstract

“…Analyzing multiple layers of molecular information can enhance diagnostic accuracy and predictive capabilities. [220][221][222][223][224] − The application of artificial intelligence (AI) and machine learning algorithms can aid in the analysis and interpretation of complex biomarker data. AI can assist in identifying patterns, predicting disease outcomes, and improving the accuracy and efficiency of cancer diagnosis.…”

Section: Perspectivesmentioning

confidence: 99%

Biomarkers for early cancer detection: A landscape view of recent advancements, spotlighting pancreatic and liver cancers

Tenchov,

Sapra,

Sasso

et al. 2024

Preprint

View full text Add to dashboard Cite

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcome thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are amongst the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant development in the field of early cancer detection biomarkers. Here we provide an overview of recent advancement in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientiﬁc information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts, cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, known as remarkably difficult to detect early, with particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers, to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of the article stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

show abstract

Advances in traditional herbal formulation based nano-vaccine for cancer immunotherapy: Unraveling the enigma of complex tumor environment and multidrug resistance

Saeed,

Zhong,

Sun

2024

International Immunopharmacology

View full text Add to dashboard Cite

Multi-omics analysis to screen potential therapeutic biomarkers for anti-cancer compounds

Cited by 5 publications

References 52 publications

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Biomarkers for early cancer detection: A landscape view of recent advancements, spotlighting pancreatic and liver cancers

Advances in traditional herbal formulation based nano-vaccine for cancer immunotherapy: Unraveling the enigma of complex tumor environment and multidrug resistance

Contact Info

Product

Resources

About