Huang, Yajue

PURPOSE To compare mortality risk among long-term survivors of high-grade serous ovarian cancer (HGSOC) with that of the general US population and to examine how mortality and recurrence trends have evolved under changing treatment approaches. MATERIALS AND METHODS This is a retrospective cohort study including patients with histologically confirmed HGSOC treated at a single referral cancer center from 1991 to 2022. Mortality risk, expressed as standardized mortality ratios (SMRs, ratio of observed deaths in the study population to expected deaths in an age-matched US population), was assessed at diagnosis and yearly on patients without events (disease persistence, recurrence, or death from any cause). RESULTS A total of 2,074 consecutive patients were included. The median follow-up was 12.5 years (IQR, 11.7-13.8). Most patients were stage III (1,396, 69.2%), 1,299 (62.8%) underwent primary cytoreductive surgery, and 1,688 (87.4%) received platinum-taxane as first-line therapy. At diagnosis, the mortality rate was 7.40 times higher than that in the general population (95% CI, 7.04 to 7.77). By 7 event-free years, the 95% CI for the SMR included 1 for the first time, and at 10 years, the SMR was 1.05 (95% CI, 0.72 to 1.49), indicating no statistically significant excess mortality compared with the general population. In those event-free at 10 years, the 5-year cumulative incidence of ovarian cancer–related deaths (8.2% [95% CI, 4.2 to 16.0]) was comparable with that of non–ovarian cancer–related deaths (6.3% [95% CI, 2.9 to 13.8]). CONCLUSION In this cohort, mortality risk steadily declined for patients who remained event-free, approaching that of the general population by 7 years after diagnosis. These results emphasize the importance of individualized, long-term follow-up to address both recurrence risk and survivorship needs.

Abstract Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as “black boxes”, lacking transparency about whether and which histomorphological patterns drive their predictions, hindering interpretability and clinical adoption. Here we propose a human-in-the-loop explanation framework, MorphoXAI, which provides both local and global interpretability for deep learning models by incorporating human-expert interpretations. At the global level, it reveals the histomorphological patterns on which the model consistently relies to distinguish between classes of WSIs, as well as the patterns associated with confusion between classes. At the local level, it indicates which of these patterns are used in the prediction of an individual WSI and which regions within the slide correspond to such patterns. We validated our method on a deep learning model trained for ovarian tumor histologic subtype prediction. The results show that our framework generates explanations that accurately reflect the histomorphology underlying the model’s predictions at both global and local levels. For interpretability and clinical utility in diagnostic contexts, human evaluation results showed that our explanations were easy to interpret, rich in diagnostic features, and directly helpful for diagnostic decision-making, thereby enhancing pathologist-AI collaboration. Our work highlights that unifying global and local explanations and grounding them in expert-interpreted morphology enhances the interpretability and verifiability of deep learning models, thereby facilitating the transparent deployment of such models in clinical practice.

Abstract Background: The tumor microenvironment (TME) plays a pivotal role in ovarian cancer (OC) progression and prognosis, while also contributing to biological differences between primary and metastatic tumors. This study examines OC TMEs to uncover associations with clinical prognosis and tumor biology by analyzing paired primary and metastatic tumors from the same patients. Methods: This study focused on 57 stage-IIIC/IV OC patients treated at the Mayo Clinic, all of whom underwent surgical debulking and adjuvant therapies. All patients provided informed consent, and the study received IRB approval. A tissue microarray (TMA) was specifically designed and constructed, containing paired primary and metastatic tissue cores from the same patients. 147 tissue cores from the constructed TMA were profiled using a 35-antibody panel, with 17 antibodies for cell phenotyping and 18 for functional state characterization. Profiling was performed using Cell DIVE, a multiplexed imaging solution at the single-cell level developed by Leica Microsystems. After cell segmentations and classifications, detailed spatial niche and regional analyses were performed at the single-cell level. Immune cell populations, as well as their TME distributions, were characterized to conduct prognostic associations and contrast primary and metastasis differences. Results: A total of 1,292,988 total cells (after excluding low-density signals and ambiguous classifications) were analyzed, with a median of 8,033 cells per core. Using spatial neighborhood analysis, 12 distinct spatial niches were identified with specific cell types and/or unique functional states. Among these, a macrophage- and fibroblast-enriched niche at the tumor-stroma interface was associated with improved overall survival (p=0.008). Another rare Treg-enriched niche, along with other immune cells, demonstrated protective effects, particularly in patients with residual macroscopic tumors after debulking surgery (p=0.05), while no significant effects were observed in those without visible residual disease (p=0.8). When comparing primary and metastatic tumors, metastatic lesions exhibited significantly increased tumor mass (p=2e-4) and a notable reduction in helper T cells (p=0.04) in tumor areas, as well as significantly increased fibroblast cells in tumor-stroma interfacing regions (p=0.002), reflecting distinct immunosuppressive and tumor-promoting shifts. Conclusion: This study reveals spatial and cellular differences in primary and metastatic OC TMEs, distribution differences linked to prognosis and surgical outcomes. These findings emphasize the potential of spatially resolved TME profiling to refine adjuvant and neoadjuvant therapeutic strategies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6266.

AbstractBackgroundObtaining a diagnosis and treating pulmonary malignancies during the same anesthesia requires either an on‐site pathologist or a system for remotely evaluating microscopic images. Cytology specimens are challenging to remotely assess given the need to navigate through dispersed and three‐dimensional cell clusters. Remote navigation is possible using robotic telepathology, but data are limited on the ease of use of current systems, particularly for pulmonary cytology.MethodsAir dried modified Wright‐Giemsa stained slides from 26 touch preparations of transbronchial biopsies and 27 smears of endobronchial ultrasound guided fine needle aspirations were scored for ease of adequacy assessment and ease of diagnosis on robotic (rmtConnect Microscope) and non‐robotic telecytology platforms. Diagnostic classifications were compared between glass slides and the robotic and non‐robotic telecytology assessments.ResultsCompared to non‐robotic telecytology, robotic telecytology had a greater ease of adequacy assessment and non‐inferior ease of diagnosis. The median time to diagnosis using robotic telecytology was 85 s (range 28–190 s). Diagnostic categories were concordant for 76% of cases in robotic versus non‐robotic telecytology and 78% of cases in robotic telecytology versus glass slide diagnosis. Weighted Cohen's kappa scores for agreement in these comparisons were 0.84 and 0.72, respectively.ConclusionsUse of a remote‐controlled robotic microscope improved the ease of adequacy assessment compared to non‐robotic telecytology and enabled strongly concordant diagnoses to be expediently rendered. This study provides evidence that modern robotic telecytology is a feasible and user‐friendly method of remotely and potentially intraoperatively rendering adequacy assessments and diagnoses on bronchoscopic cytology specimens.

AbstractOur objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high‐grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi‐institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36–3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11–2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

Abstract Background: DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT>TAT and TCG>TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. Methods: Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n=195), The Cancer Genome Atlas (TCGA) OC tumors (n=419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n=84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. Results: In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P=5e-04). These six tumors were hypermutated with a higher tumor mutation load (mean, 54.02 mutations per megabase) compared to non-POLE endometrioid OC cases (mean, 7.69 mutations per megabase; P=5e-04), and had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P=.008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations.Conclusions: From the largest cohort of RNA-seq from endometrioid OC to date (n=53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

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.

The newly proposed International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) classification of lung adenocarcinoma has emphasized the prognostic significance of histological subtyping. In this study, 2 surgical pathologists reevaluated 49 consecutive cases of invasive primary pulmonary adenocarcinomas; histological subtyping was performed according to the IASLC/ATS/ERS classification. The 2 reviewers agreed on the predominant pattern in 23 out of 32 independently reviewed cases (71.9%, k = 0.628, 95% confidence interval = 0.442-0.815). Postconsensus, a complex glandular pattern consisting of fused, closely packed glands and cribriform architecture was identified in 9 of 49 (18%) cases. This pattern has a strong association with lymphovascular invasion (78%; P = .0091), high mitotic activity (89%), and higher tumor stage (78%). Frequent association of complex glandular pattern with poor prognostic factors and its overlap with acinar pattern warrant a more detailed description of this pattern in the classification system and a large-scale study to evaluate its prognostic significance.