Publications by authors named "Tianyi You"

Advances in cancer genomics have significantly expanded our understanding of cancer biology. However, the high cost of drug development limits our ability to translate this knowledge into precise treatments. Approved non-oncology drugs, comprising a large repository of chemical entities, offer a promising avenue for repurposing in cancer therapy.

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Article Synopsis
  • Unraveling causal variants in genome-wide association studies (GWASs) is essential for understanding the genetics behind complex traits and diseases, but current tools need improvement to identify these variants accurately.
  • CAUSALdb has been enhanced to CAUSALdb2, now featuring over 15,000 updated GWAS summary statistics and implementing both LD-based and LD-free fine-mapping methods to improve the detection of causal genetic variations.
  • The updated database provides better accuracy through larger reference panels and functional annotations, enabling researchers to visualize and understand the genetic factors of complex diseases more effectively, while remaining freely accessible for continued genetic research.
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Transcriptome-wide association study (TWAS) has successfully identified numerous complex disease susceptibility genes in the post-genome-wide association study (GWAS) era. Over the past 3 years, the focus of TWAS algorithms has shifted from merely identifying associations to understanding how single nucleotide polymorphisms (SNPs) regulate gene expression, with a growing emphasis on incorporating fine-mapping techniques. Additionally, the rapid increase in GWAS summary statistics, driven largely by the UK Biobank and other consortia, has made it essential to update our webTWAS resource.

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Background: The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma.

Results: Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions.

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Article Synopsis
  • Data mining is a method used to uncover hidden relationships in data and is increasingly applied in acupuncture research in traditional Chinese medicine.
  • Recent studies over the last five years reveal significant flaws in acupuncture data mining, such as vague research parameters, lack of clarity in data retrieval methods, and insufficient evaluation of research quality.
  • The paper aims to highlight these deficiencies to enhance the methodologies used in acupuncture data mining research, ultimately improving the reliability and practicality of the findings for clinical use.
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Background: Chronic Obstructive Pulmonary Disease (COPD) is the most common respiratory disease in clinic. Traditional Chinese medicine (TCM) lung rehabilitation has gradually been valued in the field of prevention and treatment of COPD. Acupuncture, as an important part of TCM lung rehabilitation, is carried out in clinical extensively and application.

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A part of colorectal cancer which is characterized by simultaneous numerous hypermethylation CpG islands sites is defined as CpG island methylator phenotype (CIMP) status. Stage II and III CIMP-positive (CIMP+) right-sided colon cancer (RCC) patients have a better prognosis than CIMP-negative (CIMP-) RCC treated with surgery alone. However, there is no gold standard available in defining CIMP status.

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Cardiovascular dysfunction is one of the most common complications of long-term cancer treatment. Growing evidence has shown that antineoplastic drugs can increase cardiovascular risk during cancer therapy, seriously affecting patient survival. However, little is known about the genetic factors associated with the cardiovascular risk of antineoplastic drugs.

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Bevacizumab is the molecular-targeted agent used for the antiangiogenic therapy of metastatic colorectal cancer. But some patients are resistant to bevacizumab, it needs an effective biomarker to predict the prognosis and responses of metastatic colorectal cancer (mCRC) to bevacizumab therapy. In this work, we developed a qualitative transcriptional signature to individually predict the response of bevacizumab in patients with mCRC.

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Cetuximab therapy, which heavily relies on the activation of Ras pathway, has been used in KRAS, NRAS, BRAF, and PIK3CA wild-type colorectal cancer (CRC) (Ras-normal). However, the response rate only reached 60%, due to false-negative mutation detection and mutation-like transcriptome features in wild-type patients. Herein, by integrating RNA-seq, microarray, and mutation data, we developed a Ras pathway signature by characterizing KRAS/NRAS/BRAF/PIK3CA mutations to identify the hidden nonresponders from the Ras-normal patients by mutation detection.

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The progression of cancer is accompanied by the acquisition of stemness features. Many stemness evaluation methods based on transcriptional profiles have been presented to reveal the relationship between stemness and cancer. However, instead of absolute stemness index values-the values with certain range-these methods gave the values without range, which makes them unable to intuitively evaluate the stemness.

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An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Background: Microsatellite instability (MSI) accounts for about 15% of colorectal cancer and is associated with prognosis. Today, MSI is usually detected by polymerase chain reaction amplification of specific microsatellite markers. However, the instability is identified by comparing the length of microsatellite repeats in tumor and normal samples.

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Histological grading (HG) is an important prognostic factor of colorectal adenocarcinoma (CRAC): the high-grade CRAC patients have poorer prognosis after tumor resection. Especially, the high-grade stage II CRAC patients are recommended to receive adjuvant chemotherapy. Due to the subjective nature of HG assessment, it is difficult to achieve consistency among pathologists, which brings patients uncertain grading outcomes and inappropriate treatments.

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Background: Ovarian cancer (OvCa) is one of the most common malignant diseases of the female reproductive system in the world. The majority of OvCa is diagnosed with metastasis in the abdominal cavity. Epithelial-to-mesenchymal transition (EMT) plays a key role in tumor cell metastasis.

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