Yize Li


Date of Award

Spring 5-15-2023

Author's School

Graduate School of Arts and Sciences

Author's Department

Biology & Biomedical Sciences (Human & Statistical Genetics)

Degree Name

Doctor of Philosophy (PhD)

Degree Type



Kidney disease and cancer are both highly heterogeneous diseases, meaning that they exhibit significant variability in their underlying causes, mechanisms, progression, and responses to therapy. Traditional approaches to studying these diseases have focused on individual molecular or cellular pathways, which can provide limited information on the complexity of the disease. By combining multi-omics technologies, we can gain a more comprehensive understanding of the molecular and cellular changes that occur in kidney disease and cancer and identify new therapeutic targets and personalized treatment options.

As a kidney disease, clear cell renal cell carcinomas (ccRCCs) represent ~75% of RCC cases and account for most RCC-associated deaths. Inter- and intra-tumoral heterogeneity (ITH) results in varying prognoses and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single nuclei RNA-seq of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. We molecularly stratify aggressive histopathologic subtypes that may inform more effective treatment strategies. As the other high-prevalent kidney disease, autosomal dominant polycystic kidney disease (ADPKD) is characterized by extremely large kidneys due to the development and expansion of spherical cysts within the kidney that ultimately replace normal kidney parenchyma. We conducted single-nuclei (sn) RNA-seq and ATAC-seq, spatial transcriptomics (ST), co-detection by indexing (CODEX) images, and a variety of bulk sequencing technologies profiling 28 samples from 8 human ADPKD patients, to decipher the transcriptional regulation of cysts and the surrounding cystic microenvironment (CME), and gain insight into the disease progression and potential therapeutic targets of ADPKD.

Furthermore, in addition to investigating disease individually, we conduct Pan-Cancer investigations to identify differences and similarities across cancer types which is critical in understanding the basic dynamics of oncogenesis and can help inform diagnoses, prognoses, and therapies, moreover, push progress toward personalized medicine. Advances in genetics and cancer genomic research have revealed that cancers are highly heterogeneous and differ in their origins and genetic alterations. Nonetheless, there are still commonalities among cancers, such as key driver mutations, altered pathways, mutational, immune, and microbial signatures that suggest the possibility of targeting shared traits across diverse cancer types with the same therapeutic strategies. Our Pan-Cancer multi-omics analyses associate driver genes with proteomic patterns, and reveal 1) significant driver cis-regulation at the RNA, protein, and phosphoprotein levels; 2) point mutations and copy number alterations rewiring protein-protein interaction networks; 3) most cancer genes converging towards similar molecular states validated by sequence-based kinase activity profiles; 4) neoantigen burden and T-cell infiltration suggesting potential vulnerabilities to targeted therapies; and finally 5) patterns of cancer hallmarks ranging from uniform to heterogeneous across cancer types by polygenic protein abundance prediction. Overall, our work demonstrates how comprehensive proteomics across multiple tissues allows new insights linking oncogenic drivers to functional states which cannot be achieved by studying individual cancer types.


English (en)

Chair and Committee

Li Ding

Committee Members

Nima Mosammaparast, Michael Province, Nancy L. Saccone, Sheila A. Stewart,

Available for download on Monday, February 17, 2025