Unravelling Complexity

  title={Unravelling Complexity},
  author={Shyam Wuppuluri and Francisco Antonio Doria},
Toward Systems Biomarkers of Response to Immune Checkpoint Blockers
This Mini Review focuses on how an integrative view of the increasingly available multi-omics experimental data and computational approaches enables the definition of new systems-based predictive biomarkers in the tumor microenvironment.
Clinical efficacy and safety of anti-PD-1/PD-L1 inhibitors for the treatment of advanced or metastatic cancer: a systematic review and meta-analysis
A systematic review and meta-analysis of acquired data to assess the efficacy and toxicity of anti-PD-1/PD-L1 inhibitors in advanced and metastatic cancer revealed a significantly high risk for all-grade immune-related adverse events.
MiRNAs profiling and degradome sequencing between the CMS-line N816S and its maintainer line Ning5m during anther development in pepper (Capsicum annuum L.)
Findings provide a valuable information to understand miRNAs mechanism during anther development and CMS occurrence in pepper, by cleaving 77 target transcripts targeted by miR156, miR167, miRNA858 family.
Sensitizing the Tumor Microenvironment to Immune Checkpoint Therapy
A personalized biomarker-based adaptive approach to immunotherapy is proposed, whereby a sensitizing therapy is tailored to the patient's specific tumor microenvironment, followed by on-treatment verification of a change in the targeted biomarker followed by immune checkpoint therapy.
Kickstarting Immunity in Cold Tumours: Localised Tumour Therapy Combinations With Immune Checkpoint Blockade
Studies on the immunomodulatory effects of novel and experimental localised therapies, as well as the re-evaluation of established therapies, such as radiotherapy, as immune adjuvants with a focus on ICPI combinations are reviewed.
Radiomics Assessment of the Tumor Immune Microenvironment to Predict Outcomes in Breast Cancer
The RIS is a valuable instrument with which to assess the immunoscore, and offers important implications for the prognosis of breast cancer.
Validated machine learning algorithm with sub-clonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity
DASH (Deletion of Allele-Specific HLAs), a novel machine learning-based algorithm to detect HLA LOH from paired tumor-normal sequencing data, is developed and demonstrated increased sensitivity compared to previously published tools and pave the way for clinical utility.
Adopting tipping-point theory to patient transcriptomes unravels gene regulatory network dynamics
This work identifies a spatial gene-expression feature for systematic dynamics at phenotypic tipping points, which can be exploited to infer functional genetic variations and transcription factors and is compatible with noncoding RNA profiles.
Algorithmic Information Dynamics
Algorithmic Information Dynamics (AID) is an algorithmic probabilistic framework for causal discovery and causal analysis. It enables a numerical solution to inverse problems based or motivated on
Bilateral murine tumor models for characterizing the response to immune checkpoint blockade
Bilateral murine tumor models, derived from syngeneic cancer cell lines, that display a symmetrical yet dichotomous response to ICB are described that enable detailed analysis of whole tumors in a highly homogeneous background and could potentially be used for mechanistic studies using other (immuno-)therapies.