Biology subjects

Iafrate, A. J.

Publications and source records attributed to Iafrate, A. J..

5 recordsLinked to original sources

bioRxiv2026

Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistance

Precision oncology lacks scalable methods to identify the mechanisms that mediate therapeutic resistance for individual patients. Resistance often arises from focal cellular niches that are obscured by bulk profiling and costly to resolve with multi-omics. Here, we show that deep learning (DL), applied to routine histology, can localize focal tissue regions enriched for therapeutically relevant biology. Using 3111 breast cancer H&E slides with matched bulk transcriptomics, we trained weakly-supervised DL models to infer activities of immune, metabolic, and tumor-intrinsic phenotypes implicated in therapeutic resistance (AUROC>0.80; PCC>0.64). Accurate inference of these phenotypes should identify tissue regions enriched for the corresponding biological signal. Therefore, we validated phenotype inference and spatial localization with complementary analyses. Tissue-matched multiplexed immunofluorescence showed concordance between inferred immune states and corresponding cell fractions (p=0.006-0.106). Across multi-institutional cohorts, model-derived phenotypes recovered expected relationships with therapeutic outcomes (p<0.045). Finally, in a blinded evaluation, pathologists confirmed that model-derived high-attention regions were enriched for phenotype-specific morphology (p<2.408*10-5). Because evaluated phenotypes represent diverse mechanisms of resistance across therapeutic modalities, these findings provide a foundation for resistance-directed localization using therapeutic outcomes as supervision. By directing deep profiling toward model-prioritized regions, this framework could enable scalable nomination of candidate mediators of resistance for subsequent functional validation across real-world patient populations. One sentence summaryWeakly supervised deep learning localizes focal tissue regions enriched for therapeutically relevant biology in routine histology, thus offering a scalable strategy to study therapeutic resistance across large patient populations.

biophysics↗

bioRxiv2024

Two distinct durable human class-switched memory B cell populations are induced by vaccination and infection

Memory lymphocytes are durable cells that persist in the absence of antigen, but few human B cell subsets have been characterized in terms of durability. The relative durability of eight non-overlapping human B cell sub-populations covering 100% of all human class-switched B cells was interrogated. Only two long-lived B cell populations persisted in the relative absence of antigen. In addition to canonical germinal center-derived switched-memory B cells with an IgD-CD27+ CXCR5+ phenotype, a second, non-canonical, but distinct memory population of IgD-CD27- CXCR5+ DN1 B cells was also durable, exhibited a unique TP63-linked transcriptional and anti-apoptotic signature, had low levels of somatic hypermutation, but was more clonally expanded than canonical switched-memory B cells. DN1 B cells likely evolved to preserve immunological breadth and may represent the human counterparts of rodent extrafollicular memory B cells that, unlike canonical memory B cells, can enter germinal centers and facilitate B cell and antibody evolution. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/624972v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@169c77forg.highwire.dtl.DTLVardef@1a872f5org.highwire.dtl.DTLVardef@1360cforg.highwire.dtl.DTLVardef@38d7ed_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Reversible Downregulation of HLA Class I in Adenoid Cystic Carcinoma

PurposeAdenoid cystic carcinoma (ACC), a rare and lethal cancer, has shown low response rates to systemic therapies, such as cytotoxic chemotherapy and immune-checkpoint inhibitors (ICIs). Despite numerous clinical trials, some employing aggressive ICI combinations, no effective treatments for patients with recurrent or metastatic adenoid cystic carcinoma have emerged, and ACC mortality rates remain stagnant. Therefore, we aimed to characterize the ACC immune landscape to understand the poor response rates to ICIs. Experimental DesignWe leveraged automated multiplex immunofluorescence (mIF), RNA in-situ hybridization, and scRNAseq Gene Expression analysis to identify pathways supporting the cold ACC immune environment and molecularly characterize ACC tumors, adjacent normal tissues, and normal tissues from regions where ACCs arise. In vitro, we treated freshly resected ACCs with interferon-{psi} or a STING agonist. ResultsmIF demonstrated that ACC tumors are immunologically cold, with few tumor- infiltrating T-lymphocytes (TILs) and low PD-L1 expression. The most striking finding, however, was a very low HLA/B2M class I expression in almost all ACCs, which was reversible through treatment with interferon-{psi} or a STING agonist. mIF and RNAseq analyses of normal tissues revealed a p63+, NFIB+, basal duct cell population with similarly low HLA/B2M class I expression. ConclusionsLow/absent HLA/B2M expression may explain ACC tumors immunologically cold status and lack of response to ICIs. Our findings suggest that the normal cell of ACC origin exists in an HLA-low state, and that pharmacologic manipulation with immune activators, such as STING agonists, can restore HLA/B2M in ACCs, creating a path to urgently needed, effective immunotherapies.

cancer biology↗

bioRxiv2024

ERBB2/HOXB13 co-amplification with interstitial deletion of BRCA1 defines a unique subset of breast cancers

BackgroundThe HOXB13/IL17BR gene expression biomarker has been shown to predict response to adjuvant and extended endocrine therapy in patients with early-stage ER+ HER2- breast tumors. HOXB13 gene expression is the primary determinant driving the prognostic and endocrine treatment-predictive performance of the biomarker. Currently, there is limited data on HOXB13 expression in HER2+ and ER- breast cancers. Herein, we studied the expression of HOXB13 in large cohorts of HER2+ and ER- breast cancers. MethodsWe investigated gene expression, genomic copy number, mutational signatures, and clinical outcome data in the TGGA and METABRIC breast cancer cohorts. Genomic-based gene amplification data was validated with tri-colored fluorescence in situ hybridization. ResultsIn the TCGA breast cancer cohort, HOXB13 gene expression was significantly higher in HER2+ versus HER2- breast cancers, and its expression was also significantly higher in the ER- versus ER+ breast cancers. HOXB13 is frequently co-gained or co-amplified with ERBB2. Joint copy gains of HOXB13 and ERBB2 occurred with low-level co-gains or high-level co-amplifications (co-amp), the latter of which is associated with an interstitial deletion that includes the tumor suppressor BRCA1. ERBB2/HOXB13 co-amp tumors with interstitial BRCA1 loss exhibit a mutational signature associated with APOBEC deaminase activity, and copy number signatures associated with chromothripsis and genomic instability. Among ERBB2-amplified tumors of different tissue origins, ERBB2/HOXB13 co-amp with a BRCA1 loss appeared to be unique to breast cancer. Lastly, patients with ERBB2/HOXB13 co-amplified and BRCA1 lost tumors displayed a significantly shorter progression-free survival (PFS) than those with ERBB2-only amplifications. The difference in PFS was restricted to the ER- subset patients and this difference in PFS was not solely driven by HOXB13 gene expression. ConclusionsHOXB13 is frequently co-gained with ERBB2 at both low-copy number level or as complex high-level amplification with relative BRCA1 loss. ERBB2/HOXB13 amplified, BRCA1-lost tumors are strongly enriched in breast cancer, and patients with such breast tumors experience a shortened PFS.

genomics↗

bioRxiv2024

Systematic Targeting of Protein Complexes with Molecular COUPLrs

Molecular glues that engage protein complexes have transformed the study of cell biology and have had a direct impact on clinical oncology. However, the identification of new glue classes and their corresponding protein complexes has remained largely serendipitous. To overcome this challenge, we report the development of molecular COUPLrs, elaborated small molecules flanked by two cysteine-reactive warheads, as well as CONNECT, an integrated chemical proteomic platform for target deconvolution. By profiling a library of molecular COUPLrs across 13 cancer cell lines, we uncovered hundreds of proteins that can be coupled together, including in some cases in mutant selective fashions. We develop an advanced COUPLr for the oncogene EML4-ALK, which engages the fusion outside of its kinase domain, restricts protein dynamics, and disrupts EML4-ALK signaling. Collectively, molecular COUPLrs substantially expand the scope of proteins that can be chemically connected, providing an unbiased approach to identify small molecules that target protein complexes.

systems biology↗