Marcin Cieslik, PhD

I am a computational cancer geneticist and the principal investigator of an independent research laboratory in the Departments of Pathology and Computational Medicine and Bioinformatics at the University of Michigan. My program develops computational and statistical methods for cancer genomics and proteogenomics and applies them to pressing questions in cancer biology and clinical care. A consistent thread across my work is methods development. The analytic tools my laboratory builds enable biological discoveries and their clinical translation, and they are used both in my own studies and across the programs of my collaborators.

I work in three roles. As an independent investigator, I lead discovery from my own laboratory into the genomic evolution and instability of advanced cancer and into cancer immunology and immunogenetics, including the MHC/HLA system, a region long intractable to high-throughput study, using methods my group developed (Hosseini et al., 2025; Mumphrey et al., 2023). As a scientific leader of consortium-scale studies, I direct flagship projects within the NIH/NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC), including its acute myeloid leukemia effort, and I serve on the CPTAC Steering Committee and as genomics lead of the U-M Proteogenomics Data Analysis Center (Chu et al., 2026; Satpathy et al., 2025). As a collaborator, I am the analytic anchor for experimental and clinical investigators across the institution; my interdisciplinary background makes me the liaison between computational, experimental, and clinical scientists.

My methods also reach the clinic. I developed capture RNA-seq for degraded clinical samples, which became the default protocol for U-M's MI-ONCOSEQ precision-oncology program (Cieślik et al., 2015), and I served as the inaugural Director of Bioinformatics for the Division of Diagnostic Genetics and Genomics, where I built the computational platform under CLIA and CAP standards. I have published more than 100 articles in cancer genetics and bioinformatics and hold patents on experimental and computational methods that advance clinical cancer genomics.

Cancer Proteogenomics
I integrate genomic, transcriptomic, proteomic, phosphoproteomic, and metabolomic data to define tumor molecular subtypes and therapeutic vulnerabilities, resolving disease biology and clinically actionable biomarkers that genomics alone cannot. My laboratory develops the integrative analytic methods and pipelines that make consortium-scale proteogenomic studies possible, and I have led four such studies as corresponding author: Chu et al., Nature Cancer (2026), the first integrated proteogenomic and metabolomic characterization of treatment-naïve acute myeloid leukemia, integrating more than a dozen data modalities into a unified molecular classification with associated therapy targets; Satpathy et al., Cancer Cell (2025), the first international, ethnically diverse proteogenomic cohort in lung adenocarcinoma; Clark et al., Cell (2019), the founding characterization of clear-cell renal cell carcinoma; and Chowdhury et al., Cell (2024), on chemo-refractory high-grade serous ovarian cancer. Two melanoma studies on immunogenicity and proteomic determinants of checkpoint-inhibitor response are in revision at Cancer Discovery and Clinical Cancer Research. I serve on the CPTAC Steering Committee, lead the consortium's flagship AML project, co-lead the CPTAC4 prostate and melanoma projects, previously co-led the CPTAC3 renal program, and co-lead the ICPC lung group. I am Lead on the Leidos Biomedical Research contract for proteogenomic characterization of pediatric and hematologic malignancies (2025 to 2028) and Co-Investigator on U24 CA271037, the Michigan Center for Translational Cancer Proteogenomics.

Cancer Immunology and Immunogenetics
I study mechanisms of cancer immune evasion, focusing on the major histocompatibility complex (MHC/HLA), a region central to antigen presentation and immune escape that extreme polymorphism had kept beyond the reach of high-throughput analysis, and on the genomic determinants of immunotherapy response. The program rests on methods my laboratory developed first: HLAProphet for allele-level HLA proteomic quantification, HLA-Glyco for the glycosylated immunopeptidome (Bedran et al., Nature Communications, 2023, co-corresponding), and MHCnvex for copy-number and loss-of-heterozygosity calling in the MHC locus. As corresponding author I reported the distinct mutational processes shaping MHC class I versus class II selection across primary and metastatic tumors (Mumphrey et al., Cell Reports, 2023) and, with Dr. Zou, the metabolic drivers of macrophage heterogeneity in the tumor microenvironment (Li et al., Cell Reports, 2022, co-corresponding). A sustained collaboration with Dr. Pavan Reddy produced Lauder, Gondal et al., Nature Immunology (2026), establishing that MHC class I on target cells regulates CD4+ T-cell-mediated immunity, and Seike, Chu et al., Journal of Clinical Investigation (2025, co-corresponding), on mitochondrial complex II in CD4+ versus CD8+ T cells; in both, my trainees are first authors and my laboratory performed the central computational analysis. My PI funding includes the V Foundation Translational Award (MPI), the Bristol-Myers Squibb Innovation Award, the Cancer Research Institute Technology Impact Award (TCR-FISH), and an Innovation in Cancer Informatics award for HLA cancer-genetics tools; I am Co-Investigator on Dr. Raghavan's NIH/NIAID R01 on HLA class I polymorphisms and on Dr. Green and Dr. Lawrence's R01 on checkpoint blockade in melanoma.

Genomic Evolution and Instability of Advanced Cancer
I study how genomic instability and clonal evolution drive the progression, metastasis, and lethality of advanced cancer, principally advanced prostate cancer, with extensions to kidney and pediatric solid tumors, where the genomic trajectories that generate heterogeneity also generate therapy resistance. As corresponding author I reported divergent clonal evolution and early metastatic dissemination as drivers of genetic heterogeneity in metastatic castration-resistant prostate cancer (Hosseini et al., Cancer Research, 2025), extended in Rebernick, Hammer et al. (Cancer Discovery, in review), which maps the progressive genomic landscape of lethal prostate cancer using CAPSTONE, the clinico-genomic resource I built and lead at U-M. My development of copy-number-contiguity instability biomarkers is the methodological throughline and also underpins Rebernick et al., Cell Reports Medicine (2025), linking chromosomal instability to anti-GD2 immunotherapy outcomes in neuroblastoma. My independent foundation in this area includes co-first-author work defining CDK12 inactivation as an immunogenic class of advanced prostate cancer (Wu, Cieślik et al., Cell, 2018) and the ARLNC1 long-noncoding RNA in prostate-cancer progression (Zhang, ..., Cieślik et al., Nature Genetics, 2018); the genomic and structural-class analytics I contributed to FOXA1, defining three classes of activating alterations (Parolia, Cieślik et al., Nature, 2019), has grown into the independent laboratory of my former doctoral trainee Dr. Abhijit Parolia, now an Assistant Professor in the Department of Pathology and a continuing collaborator on whose Department of Defense award I serve as Co-Investigator. My PI funding includes a DoD Kidney Cancer award on phased genomics of instability and CpG hypermethylation, an NIH R03 on the topological architecture of structural variation, a DoD PCRP Idea Development Award, and the PCF Young Investigator Award; I am Co-Investigator across the U-M prostate portfolio, including the Chinnaiyan R35 and the Michigan Prostate SPORE.

Clinical and Translational Genomics, Rare Cancers, and Methods Development
I convert research-grade genomics into clinically deployable methods and infrastructure, and integrate single-cell with clinical genomics to make rare and pediatric cancers analytically tractable, since scarce and fragmented data is the reason these diseases remain underserved. My first-author capture RNA-seq method for degraded and FFPE clinical samples (Cieślik et al., Genome Research, 2015) became the default protocol for U-M's MI-ONCOSEQ precision-oncology program; related methods include the PaPy parallel-pipeline framework, the ultra-rapid NGS-processing tools used in clinical pipelines, and MiMouse, a genomic profiling panel for credentialing mouse tumor models (Cancer Research Communications, 2025). I was co-first author on the landmark integrative clinical genomics of metastatic cancer (Robinson, ..., Cieślik et al., Nature, 2017) and first author on the field-framing review of clinical cancer transcriptome profiling (Cieślik and Chinnaiyan, Nature Reviews Genetics, 2018). I am Principal Investigator of Rare-Cancer Commons (Department of Defense), a national resource integrating single-cell and clinical genomics for rare cancers, and I co-organized and team-led the inaugural NIH/NCI Childhood Cancer Data Jamboree (2025); a precision-oncology reporting platform and AI agent is pending as PI (Innovation in Cancer Informatics). Methods from my laboratory are deployed in licensed inventions that bring research-grade capability into commercial diagnostic platforms, including TAGTILE (Agilent Technologies), MI-OncoSeq 1500 (Tempus), and issued USPTO 11,746,151.