Citations

Abstract Objective Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association—Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space. Process A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members. Conclusions Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of larger datasets is crucial to emulating the success AI is achieving in other domains. It is important that AI methods do not exacerbate existing socio-economic, racial, and ethnic disparities. Genomic data standards are critical to effectively scale such technologies across institutions. With so much uncertainty, complexity and novelty in genomics and medicine, and with an evolving regulatory environment, the current focus should be on using these technologies in an interface with clinicians that emphasizes the value each brings to clinical decision-making.

ImportanceSystematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking.ObjectiveTo assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022.ExposureTreatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs], immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19.Main Outcomes and MeasuresMain outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up.ResultsOf 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR], 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13).Conclusions and RelevanceIn this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19–related thromboembolism in patients with cancer.

Abstract Background: Ovarian endometrioid carcinoma (OEC) is an uncommon, understudied histotype that is distinguished from other histotypes by unique genomic features and high hormone receptor expression. There is growing interest in the biological relevance of subtyping using immunohistochemistry (IHC). Methods: Women with primary invasive OEC diagnosed from 1989 to 2010 were retrospectively identified from the population-based Alberta Cancer Registry, Canada. Pathology slide review and IHC staining for Napsin A, TP53, and WT1 were used to reduce histologic misclassification, resulting in N=166 participants (low-stage N=138, high-stage N=28), excluding those who received neo-adjuvant chemotherapy. The following markers were stained and scored on tissue microarrays: TP53 (normal/abnormal), PMS2/MSH6 (mismatch repair proficient [MMRp]/deficient [MMRd]), PGR (loss/retained), and CTNNB1 (nuclear/cytoplasmic). Using a hierarchical decision tree by stage group (low/high), we categorized tumors as TP53 abnormal, MMRd, PGR loss, nuclear CTNNB1, and no specific immunohistochemical profile (NSIP). Distributions and five-year disease specific survival (DSS) was estimated for each group; hazard ratios (HRs) adjusted for age were estimated using Cox regression with NSIP as referent group. Results: Among low-stage cases, five-year survival was as follows: 80% for TP53 abnormal (N=10, 7%), 87% for MMRd (N=15, 11%), 80% for PGR loss (N=10, 7%), 98% for nuclear CTNNB1 (N=63, 46%), and 95% for NSIP group (N=40, 29%). Overall, IHC group was associated with DSS among low stage cases (LRT p-value=0.006), and the group with nuclear CTNNB1 had a small but statistically significant DSS advantage (HR=0.089, 95% CI 0.011-0.742, p=0.025). TP53 and PGR loss suggested shorter DSS than the referent NSIP group, but not statistically significantly so (HR=1.26 and 3.08, respectively). Among high-stage cases, five-year DSS was as follows: 57% for TP53 abnormal (N=7, 25%), 75% for MMRd (N=8, 29%), 33% for nuclear CTNNB1 (N=3, 11%), and 17% for NSIP (N=10, 36%). There were no high-stage cases in the PGR-loss group. Nuclear CTNNB1 group had a shorter DSS among high-stage cases, but this was not statistically significantly so (HR=1.16, p=0.85). Conclusion: Pending replication in additional datasets, results suggest that OEC cases in nuclear CTNNB1 or NSIP IHC groups may have a favorable prognosis in which de-escalation of therapy can be considered. In addition, abnormal TP53 and loss of PGR may identify a high-risk subset of low-stage OEC. Citation Format: Brooke Jorgensen, Stacey Winham, Julie Cunningham, Sebastian Armasu, Chen Wang, Hunter Atkinson, Bryan McCauley, Linda Kelemen, Martin Koebel, Ellen Goode. Towards a combined immunohistochemistry-based subtyping of ovarian endometrioid carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6499.

Abstract Purpose: Benign breast disease (BBD) is viewed as a non-obligate precursor stage in the development of breast cancer (BC). Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks has been routinely used in BC research. However, RNA-seq of heterogeneous bulk samples represents an averaged expression profile across all cell mixtures. Downstream analyses, such as biomarker discovery, are likely confounded by differences in cell proportions. There is a lack of research in optimizing strategies for cell type deconvolution especially for FFPE samples. We evaluated and optimized strategies for cell type deconvolution using existing single cell RNA-seq (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) breast tissue references, and applied these to a cohort of BBD FFPE samples to assess risk of subsequent BC. Methods: 7 scRNA-seq and 3 snRNA-seq public samples from women’s breast tissue were normalized using SCTransform, then integrated using Harmony to form a complete reference set. Bioinformatics evaluations examined the performance of existing statistical and deep learning-based deconvolution methods. Computational simulations were conducted to evaluate those methods on three scenarios: 1) baseline; 2) incomplete reference set; 3) FFPE artifacts. FFPE artifacts were simulated based on a generalized additive model using 7 in-house paired FFPE-fresh frozen samples. Finally, we applied the best performing method to our BBD cohort of 62 samples. Differential expression analysis adjusting for cell proportions was performed to identify transcriptomic aberrations in BBD cases. Results: snRNA-seq was more sensitive in capturing adipocytes, while scRNA-seq was more sensitive in detecting lymphocytes in breast tissue. The median number of detectable genes per cell was higher for scRNA-seq than snRNA-seq before integration (1264 vs 558). Marker gene-based regression methods (e.g. CIBERSORT) displayed higher variance and lower bias compared to methods directly using scRNA-seq data (e.g. SCDC). Incomplete reference data led to increased bias and little effect on variance. FFPE artifacts had a higher impact on performance compared to incomplete reference data. Overall, Scaden, a deep learning-based method, was the top performing method across all simulation scenarios and was especially robust to FFPE artifacts. 59 differential expressed genes (DEGs) were identified with fold change > 1.5 and p value < 0.01. DEGs involved in BC, e.g. S100A8, WNT4 and HIST1H3H, would be left out if cell proportions were not properly adjusted. Conclusions: We constructed the first complete single cell reference data for women’s breast tissue and benchmarked existing cell type deconvolution methods. Compared to analyses not adjusting for cell proportions, we observed substantial differences in perturbed genes and pathways associated with BC risk for BBD patients. Citation Format: Yuanhang Liu, Chen Wang, Stacey J. Winham, Aditya Bhagwate, Robert A. Vierkant, Julie M. Cunningham, Bryan M. McCauley, William A. Jons, Derek C. Radisky, Amy C. Degnim. Deconvolution of cell type composition in FFPE tissue: Application to benign breast disease. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4291.

Abstract Purpose: Young women’s breast cancers (YBCs), defined herein as breast cancer (BC) diagnosed at age ≤ 40 years, are etiologically and biologically distinct from postmenopausal BCs, demonstrating a higher proportion of estrogen receptor (ER) negative subtypes and a worse prognosis. Studies have not assessed whether risk factors such as recent parity and body mass index (BMI) are linked to protein expression profiles in YBCs. Accordingly, we examined protein expression assessed with GeoMx® Digital Spatial Profiling (DSP) in 640 YBCs prepared as tissue microarrays (TMAs) in the Young Women’s BC Study (YWBCS). Methods: The YWBCS is a multi-institutional cohort of 1,297 women with incident BC diagnosed at age <40 years identified through medical record review, with risk factor data collected via questionnaires. TMAs including 1,505 cores of 640 YBCs that were collected prior to therapy and were suitable for molecular analysis were evaluated for 72 markers with NanoString GeoMx DSP. Associations of log-transformed biomarker expression with BMI and time from last live birth to BC diagnosis were carried out using linear mixed modeling approaches, accounting for multiple tumor tissue cores per individual. Results: Mean age at BC was 35.5 years (range 17-40). Tumor subtypes based on clinical immunostaining were the following: luminal B 46%; luminal A 36%; triple negative 12% and HER2+ 6%. Of 72 biomarkers tested, 53 (74%) were evaluable after QC and normalization. GeoMx ER and PR protein levels were higher in luminal A and luminal B YBCs than in HER2+ and TNBC (p=2x10-94 and 2x10-52, respectively), supporting the accuracy of the GeoMx assay. Compared to nulliparas or those with most recent birth > 3 years before BC, those who gave birth ≤ 3 years prior to BC had tumors with higher expression of PR (8x10-6) and ER (p=0.006), and lower expression of BCL-2 (p=0.006). In contrast, women with last birth ≥ 6 years prior to BC had higher expression of CD8 (p=0.006) and PD-1 (p=0.001) than nulliparas and those with more recent births. Compared to women with BMI between 18.5 and 29.9, those with higher or lower BMIs had higher expression of CD34 (p=0.0003), CD4 (p=0.0009) and CD14 (p=0.001). BCL-2 expression was higher among women with BMI < 18.5 compared to those with higher values (p=0.005). Women with BMI of 30+ had higher β2-microglobulin levels than those with lower BMIs (p=0.003). Inverse dose-response associations (with higher BMI related to lower levels) were observed for expression of ER (p=0.01), pan cytokeratin (p=0.004) and four proteins in the p13K/AKT signaling pathway (p ≤ 0.01 for each). Conclusions: Preliminarily, we identify differences in hormonal and immune markers in YBCs in relation to timing of births and BMI, suggesting that these factors may contribute to etiologic heterogeneity. Multivariate modeling is ongoing to incorporate molecular subtype and other risk factors. Citation Format: Robert A. Vierkant, Laura M. Pacheco-Spann, Stacey J. Winham, Jennifer M. Kachergus, Ji Shi, Craig Snow, Fergus J. Couch, Janet E. Olson, Chen Wang, Derek C. Radisky, Amy C. Degnim, E. Aubrey Thompson, Laura C. Collins, Kathryn J. Ruddy, Ann H. Partridge, Mark E. Sherman. Associations of parity and body mass index with NanoString digital spatial protein profiling in early onset breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1000.

Abstract Objective: Endometrial cancer (EC) is the most common gynecologic malignancy and serous histology is the second most common subtype. It is associated with poorer outcomes as recurrent disease tends to be resistant to chemotherapy. Given the dearth of proven targeted therapies in this setting and the tendency for serous ECs to have homologous recombination deficiency (HRD), this study aimed to test the synergy between poly (ADP-ribose) polymerase inhibitors (PARPis) and SN38, an active metabolite of DNA topoisomerase I, irinotecan. PARPis are currently FDA approved in ovarian cancer and have their greatest efficacy in tumors with HRD while topoisomerase inhibitors are a standard chemotherapy option for recurrent cancer. Methods: A genomic instability score (GIS) was derived from low-pass whole genome sequencing-based bioinformatics analysis according to three previously reported HRD metrics: telomeric allelic imbalance, large state transitions, and loss of heterozygosity. GIS was calculated for 34 patient derived xenograft (PDX) tumors, of which eight had serous histology. PARPi, rucaparib, and SN38 were used to treat EC PDX tumors in ex vivo 3D cell culture experiments using RealTime Glo for viability after 4-5 days of drug exposure. Synergy was assessed by calculating the combination index (CI) using Chou-Talalay method. Results: GIS ≥ 42 was noted in 62.5% (5/8) of serous EC PDX tumors and only 19.2% (5/26) of non-serous EC PDX tumors. Synergy (CI < 1.0) between rucaparib and SN38 was demonstrated in 85.7% (6/7) of serous EC PDX ex vivo 3D cell culture experiments, but only 62.5% (10/16) of non-serous EC PDX tumors. Conclusions: Most serous EC PDX tumors had a high GIS, consistent with HRD, when compared to a minority of non-serous histologies. Furthermore, combination therapy of rucaparib and SN38 had a synergistic effect in almost all serous EC PDX models, while still being effective in a majority of non-serous models. Additional PDX tumors need to be assessed to establish the predictive value of a GIS on synergy between rucaparib and SN38. Further in vivo studies are also needed to confirm these ex vivo findings of synergy. Ultimately, the hope is to generate preclinical data which justifies the use of PARPis in serous ECs as monotherapy or in combination with other anticancer therapies. Citation Format: Conway Xu, Xiaonan Hou, Erik Jessen, Chen Wang, S. John Weroha. Combination therapy with poly (ADP-ribose) polymerase inhibitor in endometrial cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5495.

Multiplex immunofluorescence (MxIF) images provide detailed information of cell composition and spatial context for biomedical research. However, compromised data quality could lead to research biases. Comprehensive image quality checking (QC) is essential for reliable downstream analysis. As a reliable and specific staining of cell nuclei, 4′,6-diamidino-2-phenylindole (DAPI) signals were used as references for tissue localization and auto-focusing across MxIF staining–scanning–bleaching iterations and could potentially be reused for QC. To confirm the feasibility of using DAPI as QC reference, pixel-level DAPI values were extracted to calculate signal fluctuations and tissue content similarities in staining–scanning–bleaching iterations for identifying quality issues. Concordance between automatic quantification and human experts’ annotations were evaluated on a data set consisting of 348 fields of view (FOVs) with 45 immune and tumor cell markers. Cell distribution differences between subsets of QC-pass vs QC-failed FOVs were compared to investigate the downstream effects. Results showed that 87.3% FOVs with tissue damage and 73.4% of artifacts were identified. QC-failed FOVs showed elevated regional gathering in cellular feature space compared with the QC-pass FOVs. Our results supported that DAPI signals could be used as references for MxIF image QC, and low-quality FOVs identified by our method must be cautiously considered for downstream analyses.

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: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. Methods: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. Results: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10–2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17–3.81; P = 2.2 × 10−13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66–2.95; P = 4.1 × 10−8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10−7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10−4) in covariate-adjusted analysis. Conclusions: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. Impact: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

AbstractBackgroundCyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo‐ovarian high‐grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large‐scale, histotype‐specific validation has been performed. The hypothesis was that high‐level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.MethodsWithin the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.ResultsHigh‐level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high‐level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08‐1.47, p = .034, and HR, 1.18; 95% CI, 1.05‐1.32, p = .015, respectively). This was also true for cases with combined high‐level amplification/overexpression (HR, 1.26; 95% CI, 1.09‐1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1‐SD increase; 95% CI, 0.94‐1.06; p = .58). CCNE1 high‐level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.ConclusionThis study provides large‐scale validation that CCNE1 high‐level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.