Connection

CHAO CHENG to Prognosis

This is a "connection" page, showing publications CHAO CHENG has written about Prognosis.
Connection Strength

2.002
  1. The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma. Mol Cancer. 2024 Sep 04; 23(1):185.
    View in: PubMed
    Score: 0.113
  2. Enhancing prognostic power in multiple myeloma using a plasma cell signature derived from single-cell RNA sequencing. Blood Cancer J. 2024 03 06; 14(1):38.
    View in: PubMed
    Score: 0.109
  3. TimiGP: Inferring cell-cell interactions and prognostic associations in the tumor immune microenvironment through gene pairs. Cell Rep Med. 2023 07 18; 4(7):101121.
    View in: PubMed
    Score: 0.104
  4. A combination of intrinsic and extrinsic features improves prognostic prediction in malignant pleural mesothelioma. Br J Cancer. 2022 11; 127(9):1691-1700.
    View in: PubMed
    Score: 0.098
  5. A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction. Sci Rep. 2022 02 09; 12(1):2211.
    View in: PubMed
    Score: 0.094
  6. A lepidic gene signature predicts patient prognosis and sensitivity to immunotherapy in lung adenocarcinoma. Genome Med. 2022 01 12; 14(1):5.
    View in: PubMed
    Score: 0.094
  7. Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use. Breast Cancer Res. 2021 07 17; 23(1):74.
    View in: PubMed
    Score: 0.091
  8. Pan-cancer association of HLA gene expression with cancer prognosis and immunotherapy efficacy. Br J Cancer. 2021 08; 125(3):422-432.
    View in: PubMed
    Score: 0.090
  9. MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers. Mol Cancer Res. 2021 03; 19(3):414-428.
    View in: PubMed
    Score: 0.087
  10. Whole transcriptome signature for prognostic prediction (WTSPP): application of whole transcriptome signature for prognostic prediction in cancer. Lab Invest. 2020 10; 100(10):1356-1366.
    View in: PubMed
    Score: 0.083
  11. Systematic computational identification of prognostic cytogenetic markers in neuroblastoma. BMC Med Genomics. 2019 12 12; 12(1):192.
    View in: PubMed
    Score: 0.081
  12. Genomic Characterization of Six Virus-Associated Cancers Identifies Changes in the Tumor Immune Microenvironment and Altered Genetic Programs. Cancer Res. 2018 11 15; 78(22):6413-6423.
    View in: PubMed
    Score: 0.075
  13. A Leukocyte Infiltration Score Defined by a Gene Signature Predicts Melanoma Patient Prognosis. Mol Cancer Res. 2019 01; 17(1):109-119.
    View in: PubMed
    Score: 0.074
  14. Computational Investigation of Homologous Recombination DNA Repair Deficiency in Sporadic Breast Cancer. Sci Rep. 2017 Nov 16; 7(1):15742.
    View in: PubMed
    Score: 0.070
  15. The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients. BMC Cancer. 2017 05 02; 17(1):306.
    View in: PubMed
    Score: 0.068
  16. Contextual Refinement of Regulatory Targets Reveals Effects on Breast Cancer Prognosis of the Regulome. PLoS Comput Biol. 2017 01; 13(1):e1005340.
    View in: PubMed
    Score: 0.066
  17. Application of pharmacologically induced transcriptomic profiles to interrogate PI3K-Akt-mTOR pathway activity associated with cancer patient prognosis. Oncotarget. 2016 Dec 20; 7(51):84142-84154.
    View in: PubMed
    Score: 0.066
  18. Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer. Genome Med. 2016 10 27; 8(1):114.
    View in: PubMed
    Score: 0.065
  19. Integrative Genomic Analyses Yield Cell-Cycle Regulatory Programs with Prognostic Value. Mol Cancer Res. 2016 Apr; 14(4):332-43.
    View in: PubMed
    Score: 0.062
  20. Integrative analysis of breast cancer reveals prognostic haematopoietic activity and patient-specific immune response profiles. Nat Commun. 2016 Jan 04; 7:10248.
    View in: PubMed
    Score: 0.062
  21. Systematic analysis of hematopoietic gene expression profiles for prognostic prediction in acute myeloid leukemia. Sci Rep. 2015 Nov 24; 5:16987.
    View in: PubMed
    Score: 0.061
  22. Regulators associated with clinical outcomes revealed by DNA methylation data in breast cancer. PLoS Comput Biol. 2015 May; 11(5):e1004269.
    View in: PubMed
    Score: 0.059
  23. Integrative analysis of survival-associated gene sets in breast cancer. BMC Med Genomics. 2015 Mar 12; 8:11.
    View in: PubMed
    Score: 0.058
  24. E2F4 regulatory program predicts patient survival prognosis in breast cancer. Breast Cancer Res. 2014 Dec 02; 16(6):486.
    View in: PubMed
    Score: 0.057
  25. Predicting clinical outcomes of cancer patients with a p53 deficiency gene signature. Sci Rep. 2022 01 25; 12(1):1317.
    View in: PubMed
    Score: 0.024
  26. Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy. Clin Cancer Res. 2020 06 15; 26(12):2908-2920.
    View in: PubMed
    Score: 0.020
  27. Hypoxia-Induced VISTA Promotes the Suppressive Function of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment. Cancer Immunol Res. 2019 07; 7(7):1079-1090.
    View in: PubMed
    Score: 0.020
  28. VISTA expression on tumor-infiltrating inflammatory cells in primary cutaneous melanoma correlates with poor disease-specific survival. Cancer Immunol Immunother. 2018 Jul; 67(7):1113-1121.
    View in: PubMed
    Score: 0.018
  29. Population effect model identifies gene expression predictors of survival outcomes in lung adenocarcinoma for both Caucasian and Asian patients. PLoS One. 2017; 12(4):e0175850.
    View in: PubMed
    Score: 0.017
  30. Unsupervised feature construction and knowledge extraction from genome-wide assays of breast cancer with denoising autoencoders. Pac Symp Biocomput. 2015; 132-43.
    View in: PubMed
    Score: 0.014
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.