Resources

2019.05
ASCO 2019 | 24 Research Projects from Genecast Selected

Entitled “Caring for Every Patient, Learning from Every Patient”, ASCO 2019 will be held in Chicago, USA from May 31 to June 4.

   

This year Genecast boarded this globally renowned academic platform at ASCO with a solid scientific research capacity accumulated over the years. A total of 24 related research projects were selected for this conference (online), covering over 10 areas ranging from breast cancer, digestive tract cancer, lung cancer, liver cancer and colorectal cancer, amongst others.

    

  1. Immune biomarker expression in the tumor microenvironment in Chinese patients with esophageal squamous cell carcinoma was explored (abstract NO. e15542)

  2. Burden of copy number alterations predicts outcomes in immune checkpoint blockade treated gastrointestinal cancer patients (abstract NO. e14068)

  3. A RNA signature predicts outcomes in immune checkpoint blockade treated gastrointestinal cancer patients (abstract NO. e14071)

  4. Density of CD8+ and CD68+ lymphocyte cell infiltration is associated with clinic outcome in hepatocellular carcinoma (abstract NO. e15612)

  5. Association of the ratio of CD8+ and CD163+ lymphocytes with clinical outcome in hepatocellular carcinoma (abstract NO. e15613 )

  6. Validation of a comprehensive cancer genomic profiling assay based on massively parallel DNA sequencing (abstract NO. ) e13138

  7. A comparative analysis of RNA sequencing methods with ribosome RNA depletion for degraded and low-input total RNA from formalin-fixed and paraffin-embedded samples (abstract NO. e14654)

  8. Genetic characteristics of lung metastasis and liver metastasis from left-sided colorectal cancer with microsatellite stability (abstract NO. e15097)

  9. A novel computational tool for copy number variation detection in targeted circulating tumor DNA (abstract NO. e13051)

  10. A new method towards calculating the cancer cell fraction in cell-free DNA (abstract NO. e13053)

  11. Prediction of hepatocellular carcinoma patient survival using machine learning classification rules (abstract NO. e15649)

  12. Applying machine learning strategy for microsatellite status detection in plasma sample type (abstract NO. e14219)

  13. Transcriptional characterization of microenvironment and their prediction role for the prognosis of Hepatocellular carcinoma after surgery (abstract NO. e15650)

  14. Copy number instability (CNI) combined with CA19-9 as a biomarker for postoperative prognostic prediction of pancreatic cancer (abstract NO. e15730)

  15. Tumor copy number alteration (CNA) burden as a prognostic factor for overall survival in Chinese gastric cancers (abstract NO.e15555)

  16. Association of high copy number instability (CNI) score with prognosis in patients with gastric cancer after surgical resection (abstract NO. e15552)

  17. The mutational landscape of circulating cell-free DNA to identify neoadjuvant chemotherapy response in colorectal cancer patients (abstract NO. e15096)

  18. The mutational profile analysis of different response to neoadjuvant chemoradiation therapy in local advanced esophageal squamous cell cancer patients (abstract NO. e15560)

  19. Transcriptional characterization of immune microenvironment and their prediction role for the prognosis of local advanced lung adenocarcinoma (abstract NO. e20625)

  20. Tracking the tumor evolution of patients with recurrence of ipsilateral breast tumor (abstract NO. e12582)

  21. The mutational profile analysis of extramural vascular invasion in rectal cancer (abstract NO. e15128)

  22. The mutational landscape of MSI-H and MSS colorectal cancer (abstract NO. e15122)

  23. The cross talk between the molecular alterations and tumor immunity in the microenvironment in non-small-cell lung carcinoma (abstract NO. e20043)

  24. The molecular and immune characteristics, antitumor activity of crizotinib in non-small cell lung cancer (NSCLC) patients with MET exon 14 skipping alterations (abstract NO. e20588)