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Recent trials have shown the efficacy of trastuzumab deruxtecan (T-DXd) in HER2-negative patients, but there is not yet a way to identify which patients will best respond, especially with the inability of current HER2 IHC and FISH assays to accurately determine HER2 expression in the unamplified setting. Here, we present a heavily pre-treated patient with triple-negative breast cancer (HER2 IHC 0 who had a complete response to T-DXd. In this case, we used a CLIA-certified reverse-phase protein array-based proteomic assay (RPPA) to determine that the patient had moderate HER2 protein expression (HER2 Total 2+, 42%) and activation (HER2 Y1248 1+, 23%). Using these results, we determined that the patient may benefit from T-Dxd despite being traditionally qualified as HER2 IHC 0. These findings highlight the potential for proteomics-based assays that may more accurately quantitate HER2 and (its activation) in the HER2 unamplified/IHC 0 setting to better select patients whose tumors are classically molecularly defined as HER2 IHC 0, but still could respond to HER2-directed therapy, and give patients access to therapies which for which they otherwise would not be eligible., (© 2024. The Author(s).)

A central theme in cancer research is to increase our understanding of the cancer tissue microenvironment, which is comprised of a complex and spatially heterogeneous ecosystem of malignant and non-malignant cells, both of which actively contribute to an intervening extracellular matrix. Laser microdissection (LMD) enables histology selective harvest of cellular subpopulations from the tissue microenvironment for their independent molecular investigation, such as by high-throughput DNA and RNA sequencing. Although enabling, LMD often requires a labor-intensive investment to harvest enough cells to achieve the necessary DNA and/or RNA input requirements for conventional next-generation sequencing workflows. To increase efficiencies, we sought to use a commonplace dual preparatory (DP) procedure to isolate DNA and RNA from the same LMD harvested tissue samples. While the yield of DNA from the DP protocol was satisfactory, the RNA yield from the LMD harvested tissue samples was significantly poorer compared to a dedicated RNA preparation procedure. We determined that this low yield of RNA was due to incomplete partitioning of RNA in this widely used DP protocol. Here, we describe a modified DP protocol that more equally partitions nucleic acids and results in significantly improved RNA yields from LMD-harvested cells., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Black women are at an increased risk of developing uterine leiomyomas and experiencing worse disease prognosis than White women. Epidemiologic and molecular factors have been identified as underlying these disparities, but there remains a paucity of deep, multiomic analysis investigating molecular differences in uterine leiomyomas from Black and White patients., Objective: To identify molecular alterations within uterine leiomyoma tissues correlating with patient race by multiomic analyses of uterine leiomyomas collected from cohorts of Black and White women., Study Design: We performed multiomic analysis of uterine leiomyomas from Black (42) and White (47) women undergoing hysterectomy for symptomatic uterine leiomyomata. In addition, our analysis included the application of orthogonal methods to evaluate fibroid biomechanical properties, such as second harmonic generation microscopy, uniaxial compression testing, and shear-wave ultrasonography analyses., Results: We found a greater proportion of MED12 mutant uterine leiomyomas from Black women (>35% increase; Mann-Whitney U, P<.001). MED12 mutant tumors exhibited an elevated abundance of extracellular matrix proteins, including several collagen isoforms, involved in the regulation of the core matrisome. Histologic analysis of tissue fibrosis using trichrome staining and secondary harmonic generation microscopy confirmed that MED12 mutant tumors are more fibrotic than MED12 wild-type tumors. Using shear-wave ultrasonography in a prospectively collected cohort, Black patients had fibroids that were firmer than White patients, even when similar in size. In addition, these analyses uncovered ancestry-linked expression quantitative trait loci with altered allele frequencies in African and European populations correlating with differential abundance of several proteins in uterine leiomyomas independently of MED12 mutation status, including tetratricopeptide repeat protein 38., Conclusion: Our study shows that Black women have a higher prevalence of uterine leiomyomas harboring mutations in MED12 and that this mutational status correlates with increased tissue fibrosis compared with wild-type uterine leiomyomas. Our study provides insights into molecular alterations correlating with racial disparities in uterine leiomyomas and improves our understanding of the molecular etiology underlying uterine leiomyoma development within these populations., (Copyright © 2024 Elsevier Inc. All rights reserved.)

We employed laser microdissection to selectively harvest tumor cells and stroma from the microenvironment of formalin-fixed, paraffin-embedded head and neck squamous cell carcinoma (HNSCC) tissues. The captured HNSCC tissue fractions were analyzed by quantitative mass spectrometry-based proteomics using a data independent analysis approach. In paired samples, we achieved excellent proteome coverage having quantified 6,668 proteins with a median quantitative coefficient of variation under 10%. We observed significant differences in relevant functional pathways between the spatially resolved tumor and stroma regions. Our results identified extracellular matrix (ECM) as a major component enriched in the stroma, including many cancer associated fibroblast signature proteins in this compartment. We demonstrate the potential for comparative deep proteome analysis from very low starting input in a scalable format that is useful to decipher the alterations in tumor and the stromal microenvironment. Correlating such results with clinical features or disease progression will likely enable identification of novel targets for disease classification and interventions., Competing Interests: Conflict of interest AP, ALH, BVK, BD, TPC, RG declare that they have no known competing financial interests. DA, MW are employees of Bruker Scientific.

Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Objective: This study investigated the risk of an aggressive endometrial cancer (EC) diagnosis by race, ethnicity, and country of origin to further elucidate histologic disparities in non-Hispanic Black (NHB), Hispanic, Asian/Pacific Islander (API), American Indian/Alaskan Native (AIAN) vs. non-Hispanic White (NHW) patients, particularly in Hispanic or API subgroups., Methods: Patient diagnosed between 2004 and 2020 with low grade (LG)-endometrioid endometrial cancer (ECC) or an aggressive EC including grade 3 EEC, serous carcinoma, clear cell carcinoma, mixed epithelial carcinoma, or carcinosarcoma in the National Cancer Database were studied. The odds ratio (OR) and 95% confidence interval (CI) for diagnosis of an aggressive EC histology was estimated using logistic modeling., Results: There were 343,868 NHW, 48,897 NHB, 30,013 Hispanic, 15,015 API and 1646 AIAN patients. The OR (95% CI) for an aggressive EC diagnosis was 3.07 (3.01-3.13) for NHB, 1.08 (1.06-1.11) for Hispanic, 1.17 (1.13-1.21) for API and 1.07 (0.96-1.19) for AIAN, relative to NHW patients. Subset analyses by country of origin illustrated the diversity in the OR for an aggressive EC diagnosis among Hispanic (1.18 for Mexican to 1.87 for Dominican), Asian (1.14 Asian Indian-Pakistani to 1.48 Korean) and Pacific Islander (1.00 for Hawaiian to 1.33 for Samoan) descendants. Hispanic, API and AIAN patients were diagnosed 5-years younger that NHW patients, and the risk for an aggressive EC histology were all significantly higher than NHW patients after correcting for age. Insurance status was another independent risk factor for aggressive histology., Conclusions: Risk of an aggressive EC diagnosis varied by race, ethnicity, and country of origin. NHB patients had the highest risk, followed by Dominican, South/Central American, Cuban, Korean, Thai, Vietnamese, and Filipino descendants., Competing Interests: Declaration of competing interest Stuart S. Winkler, Chunqiao Tian, Nicholas W. Bateman, Suzanne Jokajtys, Calen W. Kucera, Christopher M. Tarney, Michael T. Richardson, Daniel Kapp, Cheng-I Liao, Megan Reddy, Michele L Cote, Timothy D. O'Connor, Nathaniel L. Jones, Matthew A. Powell, John Farley, Craig D. Shriver, Neil T. Phippen, G. Larry Maxwell and Kathleen M Darcy do not have any potential conflicts to disclose. Chad A. Hamilton reported personal fees from GlaxoSmithKline outside the submitted work. Yovanni Casablanca cited personal fees from AstraZeneca outside the submitted work. John K. Chan reported personal fees from Agenus, AstraZeneca, Eisai, Genmab, GlaxoSmithKline, Immunogen, Mersana, Molecular Targeting Technologies, Myriad, Roche, and Seagen outside the submitted work. Thomas P. Conrads is a ThermoFisher Scientific, Inc. SAB member and receives research funding from AbbVie outside the submitted work. Charles A. Leath, III received funding from the NIH UG1 CA23330 and P50 CA098252, contracted research with Agenus and Seattle Genetics, and served on a scientific advisory board for Seattle Genetics, all outside of the submitted work., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: We investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities., Methods: Non-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC)., Results: This study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p < 0.0001). After balancing the selected demographic, socioeconomic and clinical factors, survival in Black vs. White patients was no longer different in those with SCC (AHR = 1.01, 95% CI 0.97-1.06) or AC (AHR = 1.09, 95% CI = 0.96-1.24). In SCC, the largest contributors to survival disparities were neighborhood income and insurance. In AC, age was the most significant contributor followed by neighborhood income, insurance, and stage. Diagnosis of AC (but not SCC) at ≥65 years old was more common in Black vs. White patients (26% vs. 13%, respectively)., Conclusions: Histology matters in survival disparities and diagnosis at ≥65 years old between Black and White cervical cancer patients. These disparities were largely explained by modifiable factors., Competing Interests: Declaration of competing interest Chad A. Hamilton reported personal fees from GlaxoSmithKline outside the submitted work. Yovanni Casablanca cited personal fees from AstraZeneca outside the submitted work. John K. Chan reported personal fees from Agenus, AstraZeneca, Eisai, Genmab, GlaxoSmithKline, Immunogen, Mersana, Molecular Targeting Technologies, Myriad, Roche, and Seagen outside the submitted work. Thomas P. Conrads is a ThermoFisher Scientific, Inc. SAB member and receives research funding from AbbVie outside the submitted work. Charles A. Leath, III received funding from the NIH UG1 CA23330 and P50 CA098252, contracted research with Agenus and Seattle Genetics, and served on a scientific advisory board for Seattle Genetics, all outside of the submitted work. The other authors have no conflicts of interest to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: Investigate racial disparities in outcomes and molecular features in Black and White patients with endometrioid endometrial carcinoma (EEC)., Methods: Black and White patients diagnosed with EEC who underwent hysterectomy ± adjuvant treatment in SEER, National Cancer Database (NCDB), the Genomics Evidence Neoplasia Information Exchange (GENIE) project (v.13.0), and eight NCI-sponsored randomized phase III clinical trials (RCTs) were studied. Hazard ratio (HR) and 95% confidence interval (CI) were estimated for cancer-related death (CRD), non-cancer death (NCD), and all-cause death., Results: Black (n = 4397) vs. White (n = 47,959) patients in SEER had a HR (95% CI) of 2.04 (1.87-2.23) for CRD and 1.22 (1.09-1.36) for NCD. In NCDB, the HR (95% CI) for death in Black (n = 13,468) vs. White (n = 155,706) patients was 1.52 (1.46-1.58) dropping to 1.29 (1.23-1.36) after propensity-score matching for age, comorbidity, income, insurance, grade, stage, LVSI, and treatment. In GENIE, Black (n = 109) vs. White (n = 1780) patients had fewer PTEN, PIK3R1, FBXW7, NF1, mTOR, CCND1, and PI3K-pathway-related gene mutations. In contrast, TP53 and DNA-repair-related gene mutation frequency as well as tumor mutational burden-high status were similar in Black and White patients. In RCTs, Black (n = 187) vs. White (n = 2877) patients were more likely to have advanced or recurrent disease, higher grade, worse performance status and progressive disease. Risk of death in Black vs. White patients in RCTs was 2.19 (1.77-2.71) persisting to 1.32 (1.09-1.61) after matching for grade, stage, and treatment arm while balancing age and performance status., Conclusions: Differences exist in clinical presentation, outcomes, and molecular features in Black vs. White patients with EEC in real-world registries and RCTs. Targeted-drug development, strategies to modify social determinants, and diverse inclusion in RCTs are approaches to reduce disparities., Competing Interests: Declaration of interests Zachary A. Kopelman, Chunqiao Tian, Jordyn Tumas, Neil T. Phippen, Christopher M. Tarney, Erica R. Hope, Stuart S. Winkler, Suzanne Jokajtys, Calen W. Kucera, Michael T. Richardson, Daniel S. Kapp, Nathaniel L. Jones, Rodney P. Rocconi, John H. Farley, Angeles Alvarez Secord, Casey M. Cosgrove, Matthew A. Powell, Ann Klopp, Joan L Walker, Gini F. Fleming, Nicholas W. Bateman, G. Larry Maxwell, and Kathleen M. Darcy do not have any conflicts to report. John K. Chan reported personal fees from Agenus, AstraZeneca, Eisai, Genmab, GlaxoSmithKline, Immunogen, Mersana, Molecular Targeting Technologies, Myriad, Roche, and Seagen outside the submitted work. Chad A. Hamilton reported personal fees from GlaxoSmithKline outside the submitted work. Charles A. Leath, III received funding from the NIH UG1 CA23330 and P50 CA098252, contracted research with GSK and Merck, and served on a scientific advisory board for GSK and Merck, all outside of the submitted work. Thomas P. Conrads is a ThermoFisher Scientific, Inc. SAB member and receives research funding from AbbVie outside the submitted work., (Copyright © 2024 Elsevier Inc. All rights reserved.)

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition., (© 2024. The Author(s).)

Purpose: To investigate IMT use and survival in real-world stage IVB cervical cancer patients outside randomized clinical trials., Methods: Patients diagnosed with stage IVB cervical cancer during 2013-2019 in the National Cancer Database and treated with chemotherapy (CT) ± external beam radiation (EBRT) ± intracavitary brachytherapy (ICBT) ± IMT were studied. The adjusted hazard ratio (AHR) and 95% confidence interval (CI) for risk of death were estimated in patients treated with vs. without IMT after applying propensity score analysis to balance the clinical covariates., Results: There were 3164 evaluable patients, including 969 (31%) who were treated with IMT. The use of IMT increased from 11% in 2013 to 46% in 2019. Age, insurance, facility type, sites of distant metastasis, and type of first-line treatment were independently associated with using IMT. In propensity-score-balanced patients, the median survival was 18.6 vs. 13.1 months for with vs. without IMT ( p < 0.001). The AHR was 0.72 (95% CI = 0.64-0.80) for adding IMT overall, 0.72 for IMT + CT, 0.66 for IMT + CT + EBRT, and 0.69 for IMT + CT + EBRT + ICBT. IMT-associated survival improvements were suggested in all subgroups by age, race/ethnicity, comorbidity score, facility type, tumor grade, tumor size, and site of metastasis., Conclusions: IMT was associated with a consistent survival benefit in real-world patients with stage IVB cervical cancer.

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or Consensus TME . We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/., Competing Interests: T.P.C. is a Thermo Fisher Scientific, Inc. SAB member and receives research funding from AbbVie., (© 2024 The Author(s).)

Background: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics., Methods: Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor., Results: LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ )., Conclusions: Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis., (© 2024. The Author(s).)

Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods., Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test., Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10 -7 , 3 × 10 -4 , 4 × 10 -2 , respectively), and for the omental lesions on the evaluation set (p = 1 × 10 -3 ). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions., Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions., Relevance Statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines., Key Points: • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines., (© 2023. The Author(s).)

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients' tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets., (© 2023. The Author(s).)

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS 2 ) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS 2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer., (© 2023. Springer Nature Limited.)

Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABA B receptor and opioid receptors and may lead to the identification of other potential targets. These results improve our understanding of the molecular alterations of AUD across brain regions that are associated with the development and maintenance of AUD. Proteomic data from this study is publicly available at www.lmdomics.org/AUDBrainProteomeAtlas/ ., (© 2023. Springer Nature Limited.)

Objective: ATR kinase inhibitors promote cell killing by inducing replication stress and through potentiation of genotoxic agents in gynecologic cancer cells. To explore mechanisms of acquired resistance to ATRi in ovarian cancer, we characterized ATRi-resistant ovarian cancer cells generated by metronomic dosing with the clinical ATR inhibitor AZD6738., Methods: ATRi-resistant ovarian cancer cells (OVCAR3 and OV90) were generated by dosing with AZD6738 and assessed for sensitivity to Chk1i (LY2603618), PARPi (Olaparib) and combination with cisplatin or a CDK4/6 inhibitor (Palbociclib). Models were characterized by diverse methods including silencing CDC25A in OV90 cells and assessing impact on ATRi response. Serum proteomic analysis of ATRi-resistant OV90 xenografts was performed to identify circulating biomarker candidates of ATRi-resistance., Results: AZD6738-resistant cell lines are refractory to LY2603618, but not to Olaparib or combinations with cisplatin. Cell cycle analyses showed ATRi-resistant cells exhibit G1/S arrest following AZD6738 treatment. Accordingly, combination with Palbociclib confers resistance to AZD6738. AZD6738-resistant cells exhibit altered abundances of G1/S phase regulatory proteins, including loss of CDC25A in AZD6738-resistant OV90 cells. Silencing of CDC25A in OV90 cells confers resistance to AZD6738. Serum proteomics from AZD6738-resistant OV90 xenografts identified Vitamin D-Binding Protein (GC), Apolipoprotein E (APOE) and A1 (APOA1) as significantly elevated in AZD6738-resistant backgrounds., Conclusions: We show that metronomic dosing of ovarian cancer cells with AZD6738 results in resistance to ATR/ Chk1 inhibitors, that loss of CDC25A expression represents a mechanism of resistance to ATRi treatment in ovarian cancer cells and identify several circulating biomarker candidates of CDC25A low, AZD6738-resistant ovarian cancer cells., Competing Interests: Declaration of Competing Interest Nothing to declare., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Inflammatory myofibroblastic tumors (IMTs) are intermediate-grade mesenchymal neoplasms commonly characterized by chromosomal rearrangements causing constitutive activation of anaplastic lymphoma kinase (ALK) and/or ALK mutations causing reduced sensitivity to ALK tyrosine kinase inhibitors (TKI). We present a patient with an IMT who initially responded to first-line alectinib, but who later suffered disease relapse and presently survives with moderate residual disease after receiving second-line lorlatinib. Biopsy specimens were analyzed using next generation sequencing (DNA-seq and RNA-seq) and reverse phase protein microarray (RPPA) as part of an institutional Molecular Tumor Board (MTB) study. An EML4-ALK rearrangement and EGFR activation (pEGFRY1068) were present in both the primary and recurrent tumors, while a secondary ALK I1171N mutation was exclusive to the latter. EGFR signaling in the background of a secondary ALK mutation is correlated with reduced ALK TKI sensitivity in vitro, implicating an important mechanism of drug resistance development in this patient. The RPPA results also critically demonstrate that ALK signaling (ALKY1604) was not activated in the recurrent tumor, thereby indicating that standard-of-care use of third- or fourth-line ALK TKI would not likely be efficacious or durable. These results underscore the importance of real-time clinical integration of functional protein drug target activation data with NGS in the MTB setting for improving selection of patient-tailored therapy., (© The Author(s) 2023. Published by Oxford University Press.)

Importance: Disparities in survival exist between non-Hispanic Black (hereafter, Black) and non-Hispanic White (hereafter, White) patients with uterine cancer., Objective: To investigate factors associated with racial disparities in survival between Black and White patients with uterine cancer., Design, Setting, and Patients: This cohort study used data from the National Cancer Database on 274 838 Black and White patients who received a diagnosis of uterine cancer from January 1, 2004, to December 31, 2017, with follow-up through December 2020. Statistical analysis was performed in July 2022., Main Outcomes and Measures: Overall survival by self-reported race and evaluation of explanatory study factors associated with hazard ratio (HR) reduction for Black vs White patients. A propensity scoring approach was applied sequentially to balance racial differences in demographic characteristics, comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, and treatment., Results: The study included 32 230 Black female patients (mean [SD] age at diagnosis, 63.8 [10.0] years) and 242 608 White female patients (mean [SD] age at diagnosis, 63.5 [10.5] years) and had a median follow-up of 74.0 months (range, 43.5-113.8 months). Black patients were more likely than White patients to have low income (44.1% vs 14.0%), be uninsured (5.7% vs 2.6%), present with nonendometrioid histologic characteristics (46.1% vs 21.6%), have an advanced disease stage (34.1% vs 19.8%), receive first-line chemotherapy (33.8% vs 18.2%), and have worse 5-year survival (58.6% vs 78.5%). Among patients who received a diagnosis at younger than 65 years of age, the HR for death for Black vs White patients was 2.43 (95% CI, 2.34-2.52) in a baseline demographic-adjusted model and 1.29 (95% CI, 1.23-1.35) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 0.8%, 7.2%, 11.5%, 53.1%, 5.8%, 1.2%, and 20.4%, respectively, of the excess relative risk (ERR) among the younger Black vs White patients. Among patients 65 years or older, the HR for death for Black vs White patients was 1.87 (95% CI, 1.81-1.93) in the baseline model and 1.14 (95% CI, 1.09-1.19) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 3.0%, 7.5%, 0.0%, 56.2%, 10.6%, 6.9%, and 15.8%, respectively, of the ERR among Black vs White patients aged 65 years or older., Conclusions and Relevance: This study suggests that histologic subtype was the dominant factor associated with racial survival disparity among patients with uterine cancer, while insurance status represented the main modifiable factor for women younger than 65 years. Additional studies of interactions between biology and social determinants of health are merited.

Objective: Although advanced stage epithelial ovarian cancer is widely considered life-threatening, 17% of women with advanced disease will survive long-term. Little is known about the health-related quality of life (QOL) of long-term ovarian cancer survivors, or how fear of recurrence might affect QOL., Methods: 58 long-term survivors with advanced disease participated in the study. Participants completed standardized questionnaires to capture cancer history, QOL, and fear of recurrent disease (FOR). Statistical analyses included multivariable linear models., Results: Participants averaged 52.8 years at diagnosis and had survived >8 years (mean:13.5); 64% had recurrent disease. Mean FACT-G, FACT-O, and FACT-O-TOI (TOI) scores were 90.7 (SD:11.6), 128.6 (SD:14.8), and 85.9 (SD:10.2) respectively. Compared to the U.S. population using T-scores, QOL for participants exceeded that of healthy adults (T-score (FACT-G) = 55.9). Overall QOL was lower in women with recurrent vs. non-recurrent disease though differences did not reach statistical significance (FACT-O = 126.1 vs. 133.3, p = 0.082). Despite good QOL, high FOR was reported in 27%. FOR was inversely associated with emotional well-being (EWB) (p < 0.001), but not associated with other QOL subdomains. In multivariable analysis, FOR was a significant predictor of EWB after adjusting for QOL (TOI). A significant interaction was observed between recurrence and FOR (p = 0.034), supporting a larger impact of FOR in recurrent disease., Conclusion: QOL in long-term ovarian cancer survivors was better than the average for healthy U.S. women. Despite good QOL, high FOR contributed significantly to increased emotional distress, most notably for those with recurrence. Attention to FOR may be warranted in this survivor population., Competing Interests: Declaration of Competing Interest None of the authors associated with the Ovarian Cancer Consortium for Long-Term Survival have any commercial association that might pose or create a conflict of interest with the information presented in this manuscript. Further, there exist no consultancies, stock ownership, or other equity interests, patent licensing arrangements or payments for conducting or publicizing the study described in the manuscript., (Copyright © 2023. Published by Elsevier Inc.)

Background: Cyclin 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., Methods: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated., Results: High-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., Conclusion: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC., (© 2022 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors., Methods: Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed., Results: We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets., Conclusions: This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC., (© 2022. The Author(s).)

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

We present a deep proteogenomic profiling study of 87 lung adenocarcinoma (LUAD) tumors from the United States, integrating whole-genome sequencing, transcriptome sequencing, proteomics and phosphoproteomics by mass spectrometry, and reverse-phase protein arrays. We identify three subtypes from somatic genome signature analysis, including a transition-high subtype enriched with never smokers, a transversion-high subtype enriched with current smokers, and a structurally altered subtype enriched with former smokers, TP53 alterations, and genome-wide structural alterations. We show that within-tumor correlations of RNA and protein expression associate with tumor purity and immune cell profiles. We detect and independently validate expression signatures of RNA and protein that predict patient survival. Additionally, among co-measured genes, we found that protein expression is more often associated with patient survival than RNA. Finally, integrative analysis characterizes three expression subtypes with divergent mutations, proteomic regulatory networks, and therapeutic vulnerabilities. This proteogenomic characterization provides a foundation for molecularly informed medicine in LUAD., Competing Interests: Declaration of interests M.D.W., R.F.B., and C.D.S. are inventors for a provisional patent application related to findings reported in this manuscript. J.S.H.L. serves as Chief Science and Innovation Officer for Ellison Institute, LLC (paid); board of trustee for Health and Environmental Institute, Inc. (unpaid, travel support); and scientific advisory board for AtlasXomics, Inc., and ATOM, Inc. (unpaid, travel support)., (Published by Elsevier Inc.)

Background: Environmental exposure to toxicants is a major risk factor for spontaneous preterm birth (PTB, <37 weeks). Toxicants and drugs administered to patients are metabolized primarily by the cytochrome P450 (CYP450) system. Along with the adult and fetal liver, the placenta, a critical feto-maternal interface organ, expresses CYP450 enzymes that metabolize these xenobiotics. However, the contribution of the fetal membranes, another tissue of the feto-maternal interface, to the expression of CYP450 enzymes and the detoxification of xenobiotics remains unknown., Aims: This study characterized CYP450 expression and determined the functional activity of CYP450 enzymes in fetal membranes., Main Methods: RNA sequencing (RNA-Seq) of placental and fetal membrane tissues and cells was done. Differential expressions of CYP450 genes were compared and validated via reverse transcription-quantitative polymerase chain reaction (RT-qPCR) between the two tissues. The functional activity of major CYP450 enzymes was determined using a fluorophore-based enzymatic assay in the presence and absence of their corresponding inhibitors., Key Findings: With the exception of genes that regulate cholesterol metabolism, the expression profile of CYP450 genes was similar between placental and fetal membranes tissues/cells. RT-qPCR analysis confirmed these findings with significant levels of mRNA for major CYP450 genes being detectable in amnion epithelial cells (AECs) and chorion trophoblasts cells (CTCs). Biochemical analyses revealed significant CYP450 enzymatic activities that were sensitive to specific inhibitors for both AECs and CTCs, suggesting that the genes were expressed as functional enzymes., Significance: This is the first study to determine global expression of CYP450 enzymes in fetal membranes which may play a role in xenobiotic metabolism during pregnancy. Given that many women are exposed to environmental toxins or require medications during pregnancy, a better understanding of their role in metabolism is required to develop safer therapeutics and prevent adverse outcomes., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome for high-grade serous ovarian cancer (HGSOC) patients. Treatment of HGSOC patients with neoadjuvant chemotherapy, however, may select for tumor cells harboring alterations in hallmark cancer pathways including metastatic potential. This study assessed this hypothesis by performing proteomic analysis of matched, chemotherapy naïve and neoadjuvant chemotherapy (NACT)-treated HGSOC tumors obtained from patients who had suboptimal (R1, n = 6) versus optimal (R0, n = 14) debulking at interval debulking surgery (IDS)., Methods: Tumor epithelium was harvested by laser microdissection from formalin-fixed, paraffin-embedded tissues from matched, pre- and post-NACT treated tumors for twenty HGSOC patients and analyzed by quantitative mass spectrometry-based proteomics., Results: Differential analysis of patient matched pre- and post-NACT treated tumors revealed proteins associated with cell survival and metabolic signaling to be significantly altered in post-NACT treated tumor cells. Comparison of pre-NACT treated tumors from suboptimal (R1) versus optimally (R0) debulked patients identified proteins associated with tumor cell viability and invasion signaling enriched in R1 patients. We identified five proteins altered between R1 and R0 patients in pre- NACT treated tumors that significantly correlated with PFS in an independent cohort of HGSOC patients, including Fermitin family homolog 2 (FERMT2), a protein elevated in R1 that correlated with disease progression in HGSOC patients (multivariate Cox HR = 1.65, Wald p = 0.022) and increased metastatic potential in solid-tumor malignancies., Conclusions: This study identified distinct proteome profiles in patient matched pre- and post-NACT HGSOC tumors that correlate with NACT resistance and that may predict residual disease status at IDS that collectively warrant further pre-clinical investigation., (© 2022. The Author(s).)

Importance: Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics., Objective: To develop and characterize a gross morphologic classification system for HGSOC., Design, Setting, and Participants: This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021., Exposures: Gross tumor morphologic characteristics., Main Outcomes and Measures: Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared., Results: Of 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes., Conclusions and Relevance: This study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.

Objectives: A risk assessment model for metastasis in endometrioid endometrial cancer (EEC) was developed using molecular and clinical features, and prognostic association was examined. Methods: Patients had stage I, IIIC, or IV EEC with tumor-derived RNA-sequencing or microarray-based data. Metastasis-associated transcripts and platform-centric diagnostic algorithms were selected and evaluated using regression modeling and receiver operating characteristic curves. Results: Seven metastasis-associated transcripts were selected from analysis in the training cohorts using 10-fold cross validation and incorporated into an MS7 classifier using platform-specific coefficients. The predictive accuracy of the MS7 classifier in Training-1 was superior to that of other clinical and molecular features, with an area under the curve (95% confidence interval) of 0.89 (0.80-0.98) for MS7 compared with 0.69 (0.59-0.80) and 0.71 (0.58-0.83) for the top evaluated clinical and molecular features, respectively. The performance of MS7 was independently validated in 245 patients using RNA sequencing and in 81 patients using microarray-based data. MS7 + MI (myometrial invasion) was preferrable to individual features and exhibited 100% sensitivity and negative predictive value. The MS7 classifier was associated with lower progression-free and overall survival ( p ≤ 0.003). Conclusion: A risk assessment classifier for metastasis and prognosis in EEC patients with primary tumor derived MS7 + MI is available for further development and optimization as a companion clinical support tool., Competing Interests: The authors did not have any conflicts to disclose related to this research investigation. The authors provide the following disclaimer. The views expressed herein are those of the authors and do not reflect the official policy of the Uniformed Services University of the Health Sciences; the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc.; Inova Health System; the Department of Army/Navy/Air Force; the Department of Defense; or the U.S. Government. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government.

Objectives: Develop conditional survival and risk-assessment estimates for uterine serous carcinoma (USC) overall and stratified by stage as tools for annual survivorship counseling and care planning., Methods: Patients in the National Cancer Data Base diagnosed between 2004 and 2014 with stage I-IV USC were eligible. Individuals missing stage or survival data or with multiple malignancies were excluded. Five-year conditional survival was estimated using the stage-stratified Kaplan-Meier method annually during follow-up. A standardized mortality ratio (SMR) estimated the proportion of observed to expected deaths in the U.S. adjusted for year, age, and race. The relationships between prognostic factors and survival were studied using multivariate Cox modeling at diagnosis and conditioned on surviving 5-years., Results: There were 14,575 participants, including 43% with stage I, 8% with stage II, 29% with stage III, and 20% with stage IV USC. Five-year survival at diagnosis vs. after surviving 5-years was 52% vs. 75% overall, 77% vs. 81% for stage I, 57% vs. 72% for stage II, 40% vs. 66% for stage III, and 17% vs. 60% for stage IV USC, respectively (P < 0.0001). Incremental improvements in 5-year conditional survival and reductions in SMR tracked with annual follow-up and higher stage. The adjusted risk of death at diagnosis vs. after surviving 5-years was 1.15 vs. 1.40 per 5-year increase of age, 1.26 vs. 1.68 for Medicaid insurance, 3.92 vs. 2.48 for stage III disease, and 6.65 vs. 2.79 for stage IV disease, respectively (P < 0.0001)., Conclusion: In USC, the evolution of conditional survival permits annual reassessments of prognosis to tailor survivorship counseling and care planning., Competing Interests: Declaration of Competing Interest Angela C. Nolin, Chunqiao Tian, Nicholas W. Bateman, Michele L. Cote, Craig D. Shriver, Matthew A. Powell, Thomas P Conrads, G. Larry Maxwell, and Kathleen M. Darcy do not have any conflicts to disclose. Chad A. Hamilton declared his role on the Board of Directors for the Foundation for Women's Cancer. Yovanni Casablanca cited stock or stock options for Pfizer and Regeneron specifying that no payments were made to her or her institution. John K. Chan reported consulting fees from AstraZeneca and GlaxoSmithKline; payments or honoraria for lectures, presentations, speaker bureaus, manuscript writing, or educational events for AstraZeneca, Clovis, Eisai, GlaxoSmithKline, Merck, and Roche; and participation on a Data Safety Monitoring Board or Advisory Board for AbbVie, AstraZeneca, Clovis, Eisai, GlaxoSmithKline, Immunogen, Myriad, Roche and Seagen. Please also see the attached conflict of interest disclosure forms., (Copyright © 2022 Elsevier Inc. All rights reserved.)

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade., Competing Interests: Conflict of interest T. P. C. is a Thermo Fisher Scientific Advisory Board member and receives research funding from AbbVie, United States. A. E. H. receives research support from Thermo Fisher Scientific, United States. J. E. V. E. is a Bruker Software Development SAB member and receives support from Thermo Fisher Scientific, Sciex, Canada, Agilent, United States, CellenONE, and Neoteryx. Many authors are involved with private sector endeavors and actively manage competing financial interests. All the other authors declare no competing interests. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.

While BRCA1 and BRCA2 mutations are known to confer the largest risk of breast cancer and ovarian cancer, the incomplete penetrance of the mutations and the substantial variability in age at cancer onset among carriers suggest additional factors modifying the risk of cancer in BRCA1/2 mutation carriers. To identify genetic modifiers of BRCA1/2 , we carried out a whole-genome sequencing study of 66 ovarian cancer patients that were enriched with BRCA carriers, followed by validation using data from the Pan-Cancer Analysis of Whole Genomes Consortium. We found PPARGC1A , a master regulator of mitochondrial biogenesis and function, to be highly mutated in BRCA carriers, and patients with both PPARGC1A and BRCA1/2 mutations were diagnosed with breast or ovarian cancer at significantly younger ages, while the mutation status of each gene alone did not significantly associate with age of onset. Our study suggests PPARGC1A as a possible BRCA modifier gene. Upon further validation, this finding can help improve cancer risk prediction and provide personalized preventive care for BRCA carriers.

Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naïve HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naïve tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naïve HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

CARD19 is a mitochondrial protein of unknown function. While CARD19 was originally reported to regulate TCR-dependent NF-κB activation via interaction with BCL10, this function is not recapitulated ex vivo in primary murine CD8 + T cells. Here, we employ a combination of SIM, TEM, and confocal microscopy, along with proteinase K protection assays and proteomics approaches, to identify interacting partners of CARD19 in macrophages. Our data show that CARD19 is specifically localized to the outer mitochondrial membrane. Through deletion of functional domains, we demonstrate that both the distal C-terminus and transmembrane domain are required for mitochondrial targeting, whereas the CARD is not. Importantly, mass spectrometry analysis of 3×Myc-CARD19 immunoprecipitates reveals that CARD19 interacts with the components of the mitochondrial intermembrane bridge (MIB), consisting of mitochondrial contact site and cristae organizing system (MICOS) components MIC19, MIC25, and MIC60, and MICOS-interacting proteins SAMM50 and MTX2. These CARD19 interactions are in part dependent on a properly folded CARD. Consistent with previously reported phenotypes upon siRNA silencing of MICOS subunits, absence of CARD19 correlates with irregular cristae morphology. Based on these data, we propose that CARD19 is a previously unknown interacting partner of the MIB and the MIC19-MIC25-MIC60 MICOS subcomplex that regulates cristae morphology.