Shaji Kunnathu Kumar

The paper integrates coding and noncoding genome annotations to improve transcriptomic analysis, identifying clinically relevant noncoding RNAs in multiple myeloma.

The paper characterizes immune microenvironment dysregulation in multiple myeloma using single-cell data and links it to disease progression and patient outcomes.

This study analyzes whole-genome sequencing data from multiple myeloma patients to show that the timing of genetic events, not just their presence, affects clinical outcomes.

This study identifies biallelic CD38 loss as a mechanism of resistance to anti-CD38 antibodies in multiple myeloma, with specific mutations affecting antibody efficacy.

This study uses longitudinal multi-omic profiling to identify immune escape mechanisms and predictors of response in multiple myeloma.

This paper introduces a new pedigree analysis method to identify risk variants for complex diseases, applying it to Multiple Myeloma and finding two genes associated with DNA repair and chromatin remodeling.