Association of machine learning (ML)–derived histological features with transcriptomic molecular subtypes in advanced renal cell carcinoma (RCC).

Authors

null

Niha Beig

Genentech, South San Francisco, CA

Niha Beig , Shima Nofallah , David F. McDermott , Robert J. Motzer , Thomas Powles , Brian I. Rini , Hartmut Koeppen , Romain Banchereau , Miles Markey , Isaac Finberg , Geetika Singh , Limin Yu , Robert Egger , Chintan Parmar , Jake Conway , Stephanie Hennek , Daniel Ruderman , Samuel Vilchez , Mahrukh A Huseni , Jennifer Margaret Giltnane

Organizations

Genentech, South San Francisco, CA, PathAI, Boston, MA, Beth Israel Deaconess Medical Center, Dana-Farber/Harvard Cancer Center, Boston, MA, Genitourinary Oncology, Memorial Sloan Kettering Cancer Center; Weill Cornell Medical College, New York, NY, Barts Cancer Centre, Queen Mary University of London, London, United Kingdom, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, Genentech, Inc., South San Francisco, CA, Path AI, Boston, MA, Genentech Inc, South San Francisco, CA

Research Funding

F. Hoffmann-La Roche Ltd

Background: Metastatic RCC (mRCC) is a molecularly heterogeneous disease. Transcriptomic analysis in the Phase 3 IMmotion 151 (Im151) trial identified 7 molecular subtypes that showed differential outcomes to Atezolizumab+Bevacizumab (A+B) vs Sunitinib (S) treatment (Motzer, Cancer Cell 2020). Here, we present histological correlates of these subtypes as identified in whole slide images (WSI) of hematoxylin and eosin (H&E) stained tumors. Methods: ML models identified 922 H&E derived, human interpretable histological features (ML HIFs) in RCC associated with tumor and stromal (including vessels, immune cells, fibroblasts) cell and tissue morphologies, and nucleus shape. These ML HIFs were then extracted from WSI in 2 mRCC trials – Im151 (n=797) and IMmotion150 (Im150, n=203). Previously described 7 molecular subtypes were combined into 4 subgroups (Angiogenic [comprised of Angiogenic/Stromal and Angiogenic], Complement/OmegaOxidation, T-effector, and Proliferative [comprised of Proliferative and Stromal Proliferative]) for computational power. Due to low prevalence, snoRNA subset was excluded. Univariate analysis with FDR correction was applied to identify positively associated ML HIFs in each of the 4 subgroups in the Im151 WSI and then validated in Im150 subgroups. Representative ML HIFs that showed uniquely higher abundance in each molecular subgroup in both studies were dichotomized by tertiles as ‘high’ or ‘low/intermediate’ and associated with progression free survival (PFS) to fit Cox proportional hazard models in Im151 study. Results: 169 ML HIFs were differentially enriched across 3 molecular subgroups in both Im151 and Im150 data sets. Angiogenic subgroup had higher prevalence of 40 ML HIFs associated with density of endothelial cells in cancer epithelium. T-effector subtype showed higher abundance of 64 ML HIFs associated with immune cell presence in stroma. Proliferative subgroup showed higher prevalence of 40 ML HIFs associated with nuclear morphologies. No ML HIFs were uniquely associated with the Complement/OmegaOxidation subgroup. Consistent with transcriptional findings in Im151, ML HIFs that were enriched in T-effector and Proliferative subgroups showed improved PFS benefit to A+B vs S (Table). Conclusions: We identified unique histological features of RCC tumors that correlate with previously defined molecular subtypes. Our results suggest that clinically relevant RCC subtypes may be extracted directly from H&E-stained WSI and may complement gene expression based patient stratification and selection strategies.

Molecular SubgroupML HIF DescriptionA+B vs S PFS HR (95% CI)
AngiogenesisDensity of endothelial cells in tumor tissue1.14 (0.85-1.54)
T-effectorDensity of lymphocytes in cancer epithelium0.72 (0.54-0.97)
ProliferativeMean length of clear cell tumor cell nucleus perimeter0.62 (0.47-0.83)

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Abstract Details

Meeting

2024 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Genitourinary Cancer—Kidney and Bladder

Track

Genitourinary Cancer—Kidney and Bladder

Sub Track

Biologic Correlates

Citation

J Clin Oncol 42, 2024 (suppl 16; abstr 4519)

DOI

10.1200/JCO.2024.42.16_suppl.4519

Abstract #

4519

Poster Bd #

214

Abstract Disclosures