Bazzaro, Martina

3118 Background: Improved risk stratification is critically needed across multiple cancers to guide treatment decisions. This includes reducing overtreatment in Ductal Carcinoma in Situ (DCIS), addressing late recurrence risk in estrogen receptor-positive/lymph node-negative (ER+/LN-) breast cancer (BC), and refining prognosis in head & neck squamous cell carcinomas (HNSCC), and high-grade serous ovarian carcinoma (HGSOC). Tumor-infiltrating lymphocytes (TILs) reflect anti-tumor immunity, whereas tumor-associated macrophages (TAMs) polarize toward anti-tumor M1-like (CD68+) or immunosuppressive M2-like (CD163+) phenotypes. Integrating TILs with TAM polarization markers may better capture inflammatory balance and improve outcome prediction. We developed a hematoxylin and eosin (H&E)-only AI method (VAIP) to quantify TILs and virtual CD68/CD163 TAMs to develop multi-cancer based potential prognostic models. Methods: TILs were detected on H&E with HoVer-UNet, and virtual CD68 and CD163 macrophages were inferred with VISTA. In cancer regions, we computed cell densities and immune-balance ratios and trained cancer-specific Cox models with compact feature sets (DCIS 6; HGSOC 7; ER+ 4; HNSCC 4). Prognostic stratification used disease-free survival (DFS) for DCIS (N=273), HGSOC (training N=165, independent test N=220), and ER+ BC (training N=144, test N=622), and overall survival (OS) for HNSCC (N=77), reflecting clinical endpoints. Evaluation used cross-validation for cohorts without an external test set (DCIS, HNSCC) and independent training and testing when independent cohort was available (HGSOC, ER+). Results: Risk stratification performance across cancer types is in Table 1. The DCIS model used 6 features, largely TIL-macrophage contrast ratios (TIL/M2, TIL/M1). HGSOC used 7 features with a similar ratio-heavy immune-balance signature, plus macrophage-normalized density and polarization metrics (e.g., M1/N, M/N). In contrast, ER+ BC and HNSCC achieved best performance with 4 features dominated by macrophage measures, particularly M2 density and the M1/M2 ratio. Across sites, CD163-related macrophage metrics and immune-balance ratios were consistently informative. Conclusions: Integrating H&E-visible TILs with virtual CD68/CD163 TAMs enables fully automated, H&E-only prognostic biomarkers that stratify OS and DFS across multiple cancers, demonstrating consistent prognostic value in DCIS, ER+ BC, HGSOC, and HNSCC. These findings support further study of this histomorphometric risk classifier through broader external and prospective validation. Performance across cancer types. Cancer Type Cohort C-index HR [95% CI] p-value DCIS All 0.616 1.76 [1.20-2.59] <0.001 DCIS RT/No-treatment 0.624 1.94 [1.15-3.26] 0.003 HGSOC Test 0.553 1.38 [1.02-1.87] 0.030 ER+ BC Test 0.577 1.51 [1.00-2.28] 0.004 HNSCC All 0.603 1.92 [1.03-3.36] 0.012

Targeting glutamine metabolism has emerged as a novel therapeutic strategy for several human cancers, including ovarian cancer. The primary target of this approach is the kidney isoform of glutaminase, glutaminase 1 (GLS1), a key enzyme in glutamine metabolism that is overexpressed in several human cancers. A first-in-class inhibitor of GLS1, called CB839 (Telaglenastat), has been investigated in several clinical trials, with promising results. The first clinical trial of CB839 in platinum-resistant patients with ovarian cancer is forthcoming. ARID1A-mutated ovarian clear cell carcinoma (OCCC) is a relatively indolent and chemoresistant ovarian cancer histotype. In OCCC-derived cells ARID1A simultaneously drives GLS1 expression and metabolism reprograming. In ARID1A-mutated OCCC-derived mouse models, loss of ARID1A corresponds to GLS1 upregulation and increases sensitivity to GLS1 inhibition. Thus, targeting of GLS1 with CB839 has been suggested as a targeted approach for patients with OCCC with tumors harboring ARID1A mutations. Here, we investigated whether GLS1 is differentially expressed between patients with OCCC whose tumors are ARID1A positive and patients whose tumors are ARID1A negative. In clinical specimens of OCCC, we found that GLS1 overexpression was not correlated with ARID1A loss. In addition, GLS1 overexpression was associated with better clinical outcomes. Our findings have implications for human trials using experimental therapeutics targeting GLS1. Significance: GLS1 differential expression in patients with OCCC with or without ARID1A mutations is significant because a clinical trial with a GLS1 inhibitor is forthcoming. Tumors without ARID1A have low levels of GLS1 and GLS1 expression is associated to better outcome. Thus, blockade of GLS1 could be counterproductive for patients with OCCC.

Abstract Purpose: Clear cell ovarian carcinoma (CCOC) is an aggressive disease that often demonstrates resistance to standard chemotherapies. Approximately 25% of patients with CCOC show a strong APOBEC mutation signature. Here, we determine which APOBEC3 enzymes are expressed in CCOC, establish clinical correlates, and identify a new biomarker for detection and intervention. Experimental Designs: APOBEC3 expression was analyzed by IHC and qRT-PCR in a pilot set of CCOC specimens (n = 9 tumors). The IHC analysis of APOBEC3B was extended to a larger cohort to identify clinical correlates (n = 48). Dose-response experiments with platinum-based drugs in CCOC cell lines and carboplatin treatment of patient-derived xenografts (PDXs) were done to address mechanistic linkages. Results: One DNA deaminase, APOBEC3B, is overexpressed in a formidable subset of CCOC tumors and is low or absent in normal ovarian and fallopian tube epithelial tissues. High APOBEC3B expression associates with improved progression-free survival (P = 0.026) and moderately with overall survival (P = 0.057). Cell-based studies link APOBEC3B activity and subsequent uracil processing to sensitivity to cisplatin and carboplatin. PDX studies extend this mechanistic relationship to CCOC tissues. Conclusions: These studies demonstrate that APOBEC3B is overexpressed in a subset of CCOC and, contrary to initial expectations, associated with improved (not worse) clinical outcomes. A likely molecular explanation is that APOBEC3B-induced DNA damage sensitizes cells to additional genotoxic stress by cisplatin. Thus, APOBEC3B is a molecular determinant and a candidate predictive biomarker of the therapeutic response to platinum-based chemotherapy. These findings may have broader translational relevance, as APOBEC3B is overexpressed in many different cancer types.

Abstract UNC-45A, a highly conserved member of the UCS (UNC45A/CRO1/SHE4P) protein family of cochaperones, plays an important role in regulating cytoskeletal-associated functions in invertebrates and mammalian cells, including cytokinesis, exocytosis, cell motility, and neuronal development. Here, for the first time, UNC-45A is demonstrated to function as a mitotic spindle-associated protein that destabilizes microtubules (MT) activity. Using in vitro biophysical reconstitution and total internal reflection fluorescence microscopy analysis, we reveal that UNC-45A directly binds to taxol-stabilized MTs in the absence of any additional cellular cofactors or other MT-associated proteins and acts as an ATP-independent MT destabilizer. In cells, UNC-45A binds to and destabilizes mitotic spindles, and its depletion causes severe defects in chromosome congression and segregation. UNC-45A is overexpressed in human clinical specimens from chemoresistant ovarian cancer and that UNC-45A–overexpressing cells resist chromosome missegregation and aneuploidy when treated with clinically relevant concentrations of paclitaxel. Lastly, UNC-45A depletion exacerbates paclitaxel-mediated stabilizing effects on mitotic spindles and restores sensitivity to paclitaxel. Implications: These findings reveal novel and significant roles for UNC-45A in regulation of cytoskeletal dynamics, broadening our understanding of the basic mechanisms regulating MT stability and human cancer susceptibility to paclitaxel, one of the most widely used chemotherapy agents for the treatment of human cancers.