A-S.B.72: CrossPoE: Survival-Calibrated Cross-Modal Translation for Multi-Omics Under Block-Wise Missingness
In clinical cancer genomics, patients are rarely profiled across all molecular data types. Multi-omics models integrating bulk mRNA expression, miRNA, and DNA methylation hold promise for survival prediction, but block-wise missingness is the norm in practice: a patient may have RNA sequencing but no methylation data, or a dataset may lack miRNA profiling entirely. Existing approaches either fuse only observed modalities without reconstructing absent ones, or learn cross-modal latent mappings without any constraint on survival signal preservation.
We present CrossPoE, a Product-of-Experts variational autoencoder that handles modality missingness through six directional cross-modal translation heads trained jointly with a survival-preserving objective. When a modality is absent, CrossPoE synthesises a pseudo-posterior from observed modalities and injects it into the PoE fusion. Critically, translation heads are trained to match task-predictive survival scores across modality pairs, not merely approximate target latent geometry. This constraint ensures pseudo-posteriors carry survival-relevant signal under missingness, and is absent from all prior latent completion methods. The directional translation structure also enables a Jacobian-based interpretability pipeline that identifies hub latent dimensions by their structural centrality across translation paths and attributes them to input features via Integrated Gradients, with stability confirmed by fold-level majority voting.
We evaluate under RNA block missingness as the most clinically relevant stress test, given RNA's dominant independent prognostic contribution. On TCGA-BRCA (1,095 samples, 145 PFI events), CrossPoE matches HEALNet-Omics on missingness robustness, and ablation confirms the translation mechanism as the primary driver: removing translation heads increases the RNA missingness C-index decline from −0.008 to −0.043. On TCGA-KIRC (535 samples, 160 PFI events), CrossPoE significantly outperforms HEALNet-Omics, CrossAE, and PoE-VAE on RNA missingness robustness, confirmed by bootstrap CIs excluding zero.
Co-authors: Fatemeh Vafaee
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