Immune thrombocytopenia in systemic lupus erythematosus: Prevalence, risk factors, and a novel predictive model for risk assessment.

INTRODUCTION: Immune thrombocytopenia (ITP) is a potentially severe manifestation of systemic lupus erythematosus (SLE) reported in 7-40% of SLE patients. ITP has been associated with a higher risk of organ damage and mortality. OBJECTIVES: To describe which factors are associated with the presence of ITP in SLE patients. METHODS: Retrospective case-control study. Cases were defined as SLE patients who had ever developed ITP and were sex- and age-matched with two controls. A predictive model was constructed to identify SLE patients who were at risk of developing ITP. RESULTS: ITP prevalence in our SLE cohort was 8.35%. Cases had a higher frequency of hemolytic anemia, while controls had a higher prevalence of arthritis at SLE diagnosis. During SLE progression, cases tested positive for anticardiolipin, anti-ß2-glycoprotein 1, and lupus anticoagulant antibodies more frequently. Cases received mycophenolic acid and azathioprine more often than controls and had a higher SLICC/ACR score. The model demonstrated a sensitivity of 87.53%, a positive predictive value of 81.92%, a specificity of 80.50%, area under the curve of 83.92%, a F1 of 83% and an overall accuracy of 83.68%. The variables that best explain the model were hemolytic anemia, arthritis, oral ulcers, Raynaud's phenomenon, low C4, low CH50, anticardiolipin and anti-ß2GP1 antibodies. CONCLUSION: SLE patients who develop ITP have a distinct phenotype characterized by more hemolytic anemia and less arthritis at SLE onset, and higher prevalence of antiphospholipid syndrome antibodies during SLE progression. This phenotype is associated with heightened organ damage and the need for more intensive therapies and stricter follow-up. Our predictive model has demonstrated an impressive ability to identify SLE patients at risk of developing ITP.

The impact of mutational clonality in predicting the response to immune checkpoint inhibitors in advanced urothelial cancer.

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment and can result in complete remissions even at advanced stages of the disease. However, only a small fraction of patients respond to the treatment. To better understand which factors drive clinical benefit, we have generated whole exome and RNA sequencing data from 27 advanced urothelial carcinoma patients treated with anti-PD-(L)1 monoclonal antibodies. We assessed the influence on the response of non-synonymous mutations (tumor mutational burden or TMB), clonal and subclonal mutations, neoantigen load and various gene expression markers. We found that although TMB is significantly associated with response, this effect can be mostly explained by clonal mutations, present in all cancer cells. This trend was validated in an additional cohort. Additionally, we found that responders with few clonal mutations had abnormally high levels of T and B cell immune markers, suggesting that a high immune cell infiltration signature could be a better predictive biomarker for this subset of patients. Our results support the idea that highly clonal cancers are more likely to respond to ICI and suggest that non-additive effects of different signatures should be considered for predictive models.