Epithelial ovarian cancer (EOC) is the deadliest gynecologic cancer, due to asymptomatic early stages, vague symptoms in later stages, and limited clinical tools. Despite distinct clinicopathologic features, all EOC histotypes typically receive identical primary treatment, and are often studied as a single entity. We analyzed the proteome of 244 patients and identified differentially abundant proteins (DAPs) with and without stage specificity across histotypes and constructed panels of DAPs to distinguish histotypes in both early and late stages. Survival analysis was performed to find proteins associated with clinical outcomes, and enrichment analysis was conducted to reveal biological processes connected to prognosis and the proteins involved. Here we find DAPs without (e.g. S100A1, AGR2, CTH) and with (TSPYL, VWA2, GPC6, S100P) stage-specificity for each histotype. Survival analysis revealed histotype- and stage-specific prognostic markers (e.g., EXO3CL2, PPIL6, GYG1, GAPDH), while biological process enrichment highlighted pathways underlying clinical outcomes. Our findings provide novel diagnostic and prognostic biomarker candidates and insights into mechanisms driving EOC progression with histotype- and stage-specificity. This may aid the development of improved clinical tools for detection, patient stratification, and targeted therapies in EOC.

Three-dimensional (3D) cancer spheroids mimic key morphological and biological features of solid tumors, providing a valuable model for evaluating drug responses. Here, we investigated whether intrinsic cancer stem cell composition and tumor subtype determine spheroid formation capacity, transcriptional profiling, and therapeutic response in breast cancer cell lines. Using the liquid overlay technique, we optimized conditions for reproducible spheroid generation using 10 human cancer cell lines derived from breast cancer, glioblastoma, and malignant melanoma. Spheroid morphology and growth dynamics were assessed over a 20-day period, while breast cancer stem cell abundance was evaluated in 2D monolayer cultures and 3D spheroids using immunohistochemistry and flow cytometry. RNA sequencing (RNA-seq) transcriptomic profiling and drug responses to bortezomib+nedaplatin following 24- and 72-hour exposure were compared between both culture systems. Optimized conditions yielded compact spheroids (5/10 cell lines), loose aggregates (3/10), and no spheroid formation (2/10). Compact spheroids (mean ± SEM, 576 ± 18 μm) and those derived from triple-negative breast cancers (TNBCs; 550 ± 19 μm) were significantly smaller than loose aggregates (822 ± 36 μm) and non-TNBC-derived spheroids (934 ± 41 μm), respectively. RNA-seq demonstrated that transcriptional variation was primarily driven by intrinsic differences between cell lines rather than culture conditions. However, spheroid-forming cells induced distinct gene expression patterns enriched in extracellular matrix remodeling, developmental pathways, and stemness-related genes. In total, 1478 differentially expressed genes were associated with spheroid formation. TENM4 (Teneurin Transmembrane Protein 4) was the only consistently deregulated gene in both spheroid-forming breast cancer models, showing up to 4.9-fold and 2.6-fold higher expression in HCC1806 and BT-474 spheroids, respectively. Consistent with the transcriptomic findings, immunohistochemical analysis demonstrated increased TENM4 protein expression, predominantly localized to the spheroid cores. Drug screening further demonstrated increased chemoresistance in 3D spheroids, with up to 7.5-fold higher viability in TNBC spheroids following bortezomib+nedaplatin treatment. Taken together, these findings highlight molecular and cellular determinants of spheroid formation in breast cancer cell lines, including stemness-associated features and upregulation of TENM4. Our results further demonstrate that intrinsic tumor subtype shapes spheroid morphology, transcriptional profiles, and drug response, providing novel insight into the mechanisms underlying 3D growth and chemoresistance that may help inform future therapeutic strategies.

Triple-negative breast cancer (TNBC) is an aggressive subtype commonly treated with chemotherapy and radiotherapy, administered preoperatively as neoadjuvant chemotherapy (NACT) or postoperatively as adjuvant treatment (AT; defined here as adjuvant chemotherapy [ACT] with or without adjuvant radiotherapy [ART]). As NACT is increasingly favored, the relative survival outcomes of these approaches and the added benefit of postoperative therapy after NACT remain uncertain. This study aimed to assess their impact on survival. In this nationwide registry-based cohort study, data for women diagnosed with cT1–2N0M0 TNBC in Sweden between 2007 and 2021 were retrieved from the Swedish National Quality Register for Breast Cancer. Survival outcomes for patients receiving NACT ± AT were compared with those receiving AT only. Propensity score matching (1:1) was performed, adjusting for age, clinical T-stage, and comorbidity. Overall survival (OS) and breast cancer-specific survival (BCSS) were estimated using Kaplan–Meier and Cox proportional hazards models. Of 3747 eligible patients, 711 received NACT ± AT and 3036 received AT alone. Median follow-up for BCSS was 3.61 years (IQR 2.37–5.50) for NACT and 6.95 years (IQR 4.36–9.62) for AT. After matching, 711 patients remained in each group. Both prior and post matching, 5-year OS and BCSS did not differ significantly between AT and NACT. These findings remained consistent after adjustment for potential confounders. OS and BCSS were similar between AT and NACT. These findings suggest that chemotherapy sequencing was not associated with a detectable survival difference, although treatment selection should be individualized and evaluated in the context of contemporary regimens.

Epithelial ovarian cancer (EOC) is a heterogenous disease with frequent late-stage diagnosis and high mortality rates, for which no reliable screening tests exist. In recent years, epigenetic biomarkers in the form of DNA methylation in CpG-rich regions have gained increased attention in the scientific community due to their robust nature and accessibility, allowing for diagnosis without the need for invasive surgery. In this study, we investigated the aberrant methylation of promoter regions in early stage EOC through non-parametric methods, with the purpose of characterizing candidate epigenetic biomarkers. The approach was used on a cohort of early stage EOC samples, and results were compared to existing programs for differential methylation. Significant regions were then used to construct a CpG panel for stratifying EOC histotypes through predictive classification in external data. Identified promoter regions were highly reproducible across cohorts, and the constructed CpG model stratified histotypes in external cohorts through predictive classification. Comparisons against other DMP and DMR callers showed a degree of homogeneity between results but also revealed promoter regions that were overlooked despite clear signs of aberrant methylation. Finally, EOC histotypes were found to differ in their methylation distribution types, and results indicate that methods sensitive to non-normally distributed data may be poorly suited to compare groups with different distribution types. The non-parametric approach identified aberrantly methylated promoter regions that were highly reproducible across cohorts. Results from predictive classification indicate that these regions may be useful for the purpose of EOC histotype stratification.

Lemur tyrosine kinase 3 (LMTK3) has been implicated in cancer prognosis and progression. While its role in early-stage epithelial ovarian cancer (EOC) has been explored, the dynamics of its subcellular expression across the disease spectrum remain unclear. LMTK3 protein expression was assessed by immunohistochemistry on tissue microarrays comprising benign, borderline, and malignant ovarian tumors (n = 532). Nuclear and cytoplasmic staining were quantified via histochemical scores (H-scores) and analyzed in relation to histotype, disease stage, and overall survival. LMTK3 was broadly expressed across all tumor types, with predominant nuclear localization in benign and borderline lesions. Malignant tumors exhibited increased cytoplasmic expression and a stronger nuclear-cytoplasmic correlation (ρ = 0.73, p < 0.001), indicating altered spatial regulation during tumor progression. Within malignant EOC, LMTK3 expression patterns varied significantly by histotype and disease stage, reflecting context-dependent subcellular regulation. High nuclear expression was associated with better survival in early-stage EOC (adj. hazard ratio [HR] 0.33, p < 0.001), while cytoplasmic dominance suggested a favorable outcome in advanced-stage cases in multivariable analysis (HR = 0.53, p = 0.047). LMTK3 expression and subcellular localization evolve during ovarian tumorigenesis. These patterns carry stage-specific prognostic implications, supporting LMTK3 as a spatially resolved biomarker for EOC stratification.

Background: Hornerin (HRNR) is part of the S100-fused protein family and has been linked to poorer prognosis in various cancers, though the mechanisms remain unclear. This study aimed to explore the role of HRNR in ovarian cancer. Methods: We conducted proteomic analysis (n = 252) and RNA sequencing (n = 96) on primary ovarian carcinomas to evaluate HRNR expression across different histotypes, survival outcomes, and to identify genetic variants in the HRNR gene. We also assessed HRNR levels in both chemosensitive and chemoresistant ovarian cancer cell lines, as well as in serum samples at different disease stages. Results: Our findings revealed that HRNR levels were significantly higher in clear cell and mucinous ovarian carcinomas compared to high-grade serous carcinomas, with elevated expression associated with shorter survival. Additionally, HRNR levels increased in sera from late-stage patients compared to those in early stages. We identified several potentially harmful genetic variants in exon 3 of HRNR in patients with high-grade serous carcinoma, including a translocation of a 900 bp fragment from exon 3 to a region between exons 1 and 2. Chemoresistant ovarian cancer cells exhibited higher HRNR levels than chemosensitive cells. Silencing HRNR using siRNA markedly enhanced the cytotoxic effects on all tested ovarian cancer cells. Conclusions: HRNR plays a significant role in ovarian cancer with potential to serve as a prognostic marker. Additionally, targeting HRNR expression may offer therapeutic benefits, particularly for patients with chemoresistance or specific HRNR genetic variants, highlighting the need for further investigation in the management of ovarian cancer. Significance: Hornerin (HRNR) is linked to poor prognosis in various cancers, but its role in ovarian cancer has been underexplored. Our study shows that HRNR expression is significantly higher in clear cell and mucinous ovarian carcinomas compared to high-grade serous carcinomas, correlating with shorter survival. Elevated HRNR levels in late-stage patients suggest its potential as a prognostic marker. We also identified harmful genetic variants in HRNR, including a novel translocation, which may affect disease progression. Targeting HRNR could enhance chemotherapy effectiveness, particularly for patients with HRNR genetic variants, positioning it as a promising biomarker and therapeutic target in ovarian cancer.

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, yet clinical tools for diagnosis, prognosis, and treatment remain limited, and molecular profiling of histotypes is lacking. Here, we leverage proteomic data to further stratify four main EOC histotypes, borderline (BL) and benign (B) tumors, and identify candidate prognostic and diagnostic biomarkers. Using proteomic data from 300 patient samples, we identified differentially abundant proteins (DAPs) such as SNCG, S100A1, VWA2, AGR2, CTH, and SPINK1 and biomarker panels to stratify the tissues. Enrichment of biological processes profiled histotypes and involvement of DAPs. Survival analysis identified candidate biomarkers predicting overall- and disease-specific survival with histotype-specificity. Of these, GLYR1, RPL12, GDPGP1, and POLR2M were associated with favorable outcomes, while SDF4, PPP3CC, EIF2AK2, and STX6 were linked to unfavorable outcomes. Collectively, these findings provide histotype-specific attributes for known and EOC biomarkers that may serve as clinical tools for EOC diagnosis and treatment decisions.

Despite advances in cancer treatments, epithelial ovarian cancer (EOC) remains the leading cause of death among gynecologic cancers. EOC is stratified into five main histopathological subtypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), endometrioid carcinoma (EC), clear cell carcinoma (CCC), and mucinous carcinoma (MC). However, personalized treatment strategies and reliable biomarkers for all histotypes remain elusive. Building on our previous work with early-stage EOC, we aim to explore diagnostic and prognostic biomarkers in advanced-stage EOC, updated to the latest World Health Organization classification guidelines from 2020, using comprehensive transcriptomic profiling from total RNA sequencing of 146 EOCs. Differential expression analysis identified top 9 histotype-specific gene panels for HGSC, CCC, MC, and EC, including S100A1 (HGSC), ARID3A (CCC), LGALS4 (MC), and PAX9 (EC). We also identified gene candidates associated with overall survival and disease-specific survival, reflecting both favorable (e.g., OTOF, EEF1E1-BLOC1S5, and STAC3) and unfavorable (e.g., SMOC1, GDPGP1, EPRS1) clinical outcome. Additionally, enrichment analysis revealed tumor progression-related pathways unique to each histotype, offering insights into the molecular mechanisms underlying disease progression and potential therapeutic targets. These findings provide valuable insights into the molecular landscape of advanced-stage EOC, paving the way for more effective diagnostic and prognostic tools across diverse histotypes.

HER2-targeted therapies have improved survival in HER2-positive breast cancer, and recent data suggest potential benefits for patients with HER2-low tumors (defined as immunohistochemistry (IHC) 1 + or 2 + and, in situ hybridization (ISH)-negative). HER2-low tumors are heterogenous, spanning the hormone receptor-positive and triple-negative subtypes. Assessing HER2-low and HER2-ultralow status remains challenging, especially across specimen types. This study aims to (1) compare HER2 assessment using conventional microscopy, digital pathology, and an artificial intelligence (AI) model, and (2) investigate changes in HER2-low status between core biopsies, surgical specimens, and metastases. IHC slides from 47 HER2-low advanced breast carcinomas were analyzed using conventional microscopy, digital pathology, and an AI model developed on Aiforia® Create. HER2 statuses were categorized as low, ultralow (score 1 + in 1–10

To evaluate differences in clinical outcomes, treatments received, recurrence, and sociodemographic characteristics in patients with triple-negative breast cancer (TNBC) classified as invasive lobular carcinoma (TNBC–ILC) or invasive carcinoma of no special type (TNBC–NST). Using national registry data, we conducted a retrospective, population-based cohort study of 6449 women diagnosed with primary TNBC (stratified by histological subtype) in Sweden (2007–2021). Clinical and treatment data were analyzed using descriptive statistics, logistic regression, machine learning (Boruta/XGBoost), and Cox proportional hazards models adjusted for patient age, tumor size, grade, nodal status, comorbidities, and receipt of adjuvant chemotherapy (ACT). TNBC–ILC accounted for 2.7

INTRODUCTION:Patients with cancer and comorbidities often experience a longer time-to-diagnosis and significantly worse clinical outcomes. Here, we evaluate the association between age, Charlson Comorbidity Index (CCI), treatment given, and patient survival, thereby identifying common non-breast cancer-related causes of death in patients with triple-negative breast cancer (TNBC). MATERIALS AND METHODS:Population-based registry data were retrieved for patients diagnosed with primary invasive TNBC in Sweden between 2007 and 2021 (n = 7145). Multivariable Cox regression analyses were performed for disease-specific survival and overall survival was calculated using a landmark time set at six months post-diagnosis, the likely timeframe for treatment initiation. Multivariable logistic regression models were computed for age, comorbidity, and treatment. Weighted CCI (CCIw) was stratified into CCIw 0, CCIw 1-3, and CCIw 4-10. RESULTS:Approximately 42 % of patients were ≥ 65 years of age and 30 % had comorbidities (27 % CCIw 1-3 and 3 % CCIw 4-10). Two or more comorbidities were common in patients ≥65 years. Patients in the CCIw 4-10 group were significantly older (72 years vs. 68 years for CCIw 1-3 vs. 58 years for CCIw 0) and had locoregional spread and larger tumors. Individuals with comorbidities were less likely to receive neoadjuvant chemotherapy, breast-conserving surgery, or postoperative treatment, and had a higher risk of death due to non-breast cancer-related causes. Patients ≥75 years had a higher risk of breast cancer-related death up to eight years after the landmark time and death from other causes thereafter. Furthermore, older (≥75 years) and patients with comorbidities had the lowest five-year survival probabilities. Other neoplasms (26 %; e.g., lung, pancreas, and ovarian cancer) and cardiovascular disease (24 %) were the leading causes of non-breast-cancer-related death, particularly in patients ≥50 years of age. DISCUSSION:Patients with TNBC and comorbidities are less likely to receive specific treatment modalities and experience worse survival outcomes. Other malignant neoplasms are the leading cause of death for patients ≥50 years of age.

Breast cancer immune phenotypes influence treatment response and clinical outcomes, yet their ancestry-specific variations remain underexplored. Here, we analyzed transcriptomic data from over 13,000 breast tumors across six ancestry groups to characterize immune-stromal profiles and their association with ancestry, biological features, treatment response, and survival outcomes. Expression patterns were validated by spatial proteomics and immunohistochemistry. K-means clustering consistently identified three immune phenotypes (Hot, Moderate, or Cold) that varied significantly by ancestry, age, molecular subtype, and prognosis. Logistic regression and ancestry-associated analyses revealed that while immune phenotypes were primarily driven by PAM50 subtype, age, and disease stage, notable ancestry-related differences persisted, with European ancestry generally exhibiting higher immune and stromal activity across breast cancer subtypes. Hot tumors, enriched in the Basal-like and HER2 subtypes, were associated with younger age, higher immune infiltration, and improved overall survival. African ancestry was linked to elevated immune scores and upregulation of BTLA-mediated T cell co-inhibition, suggesting sensitivity to immunotherapy. European and East Asian tumors showed stromal enrichment, particularly inflammatory and myofibroblastic cancer-associated fibroblasts, associated with poor prognosis. Core immune activation genes (e.g., CD3, CD2, and CXCL10) were conserved, while ancestry-specific signatures and chemokine signaling were identified. This study uncovers both shared and ancestry-specific immunogenomic features of breast cancer, highlighting the role of ancestry and other biological features in shaping the tumor immune microenvironment. These findings re-emphasize the need for population-informed approaches in breast cancer immunotherapy and biomarker development, to ensure equitable precision oncology strategies across global populations.

131I (iodide) accumulates in the thyroid and may affect thyroid tissue. Mechanisms behind such effects are not known. The aim was to investigate early changes in protein expression in thyroid and plasma from mice injected with 131I as iodide. Female Balb/c nude mice were i.v. injected with 0 or 490 kBq 131I and killed after 24 h. Thyroid and blood samples were collected from each animal. Protein levels were determined by mass spectrometry. Data are available via ProteomeXchange with identifier PXD062861. Altogether, 17 and 20 proteins showed statistically significant altered levels in thyroid gland and plasma, respectively, after 131I exposure. Most of these proteins had decreased and increased levels in thyroid and plasma, respectively. Few of them were previously proposed radiation responsive proteins. Functional annotation suggests impact on haematopoiesis, reduced oxygen levels, and hypothyroidism. The role of CHIA and PGAM2 in radiation-induced response should be further examined, together with identification and validation of biomarkers of 131I exposure.

Epithelial ovarian cancer (EOC) is a deadly and heterogenous disease comprising five major histotypes: clear cell carcinoma (CCC), endometrioid carcinoma (EC), low- and high-grade serous carcinoma (LGSC, HGSC), and mucinous carcinoma (MC). Despite this heterogeneity, EOC is often treated as a homogenous disease, and reliable screening tests are lacking. Although progress has been made, there is a pressing need for biomarkers to refine patient stratification, guide treatment, and improve outcomes. Here, we elucidated the relationship between DNA methylation and gene expression patterns in EOC to identify histotype-specific biomarkers. Differential DNA methylation and gene expression analyses were performed for 86 early-stage EOC samples after histopathological reclassification stratified by histotype. The correlation between DNA methylation and gene expression was examined, and histotype-specific biomarkers were identified. Hierarchical clustering and predictive machine learning modeling were employed to assess the performance of the histotype-specific biomarkers using four external cohorts. EOC histotypes exhibited distinct epigenetic, transcriptional, and functional profiles, with candidate histotype-specific biomarkers such as CTSE and VCAN effectively distinguishing CCC, HGSC, and MC on the transcriptional level. Gene expression for the candidate biomarkers was found to be reproducible across external cohorts, with histotype-specific differences remaining homogenous. This study identified promising histotype-specific biomarkers for EOC using integrative transcriptomic and epigenomic analysis. Furthermore, these findings indicate that additional stratification or potential reclassification of the EC histotype is warranted in future studies.

This study explores the role of titin, a giant muscle protein, in the progression of epithelial ovarian cancer (EOC). We examined titin levels in tissues and sera from EOC patients across stages I-IV and in chemoresistant EOC cells. Tissue samples underwent immunohistochemistry, and serum titin levels were measured using ELISA. Quantitative real-time PCR analyzed titin mRNA in cell lines, including chemosensitive, chemoresistant, and normal ovarian cells. Notably, elevated titin levels were detected in 90.9% of stage I tissues compared to only 14.3% of stage III and IV tissues. Serum titin levels were consistently decreased across all stages relative to healthy controls, with a gradual decrease in expression from stages I to IV. Additionally, titin levels were significantly higher in normal ovarian epithelial cells compared to both chemosensitive and chemoresistant EOC cells, albeit significantly higher in chemosensitive than chemoresistant cells. These findings suggest the possible role of decreased titin levels as a marker for therapeutic intervention, particularly in advanced-stage and chemoresistant EOC. Further elucidation of the mechanisms underlying attenuated titin expression holds promise for advancing our understanding of ovarian cancer pathogenesis.

Introduction Despite a steady decline in tobacco smoking, head and neck cancer (HNC) incidence rates are on the rise. Therefore, novel risk factors for HNC are needed to identify at-risk patients at an early stage. Here, we used genetic, clinical, lifestyle, and sociodemographic data from UK Biobank (UKB) to evaluate the relative importance of known risk factors for HNC and identify novel predictors of HNC risk. Methods All participants in the UKB between 2006 and 2021 were stratified into HNC cases and controls at baseline (cases: n = 534; controls: n = 501833) or during follow-up (cases: n = 1587; controls: n = 500246). A cross-sectional description of risk factors (clinical characteristics, lifestyle and sociodemographic) for HNC at baseline was performed, followed by multivariate Cox regression analysis (adjusted for age and sex) and gradient boosting machine learning to determine the relative importance of predictors (phenotypic predictors and SNPs) of HNC development after baseline. Results In addition to known risk factors for HNC (age, male sex, smoking and alcohol consumption habits, occupation), we show that smoking cessation at ≤ 40 years of age is the strongest predictor of HNC risk. Although SNPs may play a role in HNC development, a predictive model containing phenotypic variables and SNPs (C-index 0.75) did not significantly outperform a model containing the phenotypic predictors alone (C-index 0.73). Conclusion Taken together, this study demonstrates that phenotypic variables such as past tobacco smoking habits, occupation, facial pain, education, pulmonary function, and anthropometric measures can be used to predict HNC risk.

Background and purpose: BRCA-related hormone receptor (HR)-negative breast cancers (BC) are reported to have aggressive tumor biology but also exhibit chemosensitivity. However, the impact of BRCA1/2 pathogenetic variants (PV) on BC outcomes remains unclear. This study compares survival outcomes for HR-negative BC between BRCA carriers and noncarriers. Patients/material and methods: From 489 female BRCA-carriers prospectively registered in western Sweden (1996–2017), those with primary HR-negative BC who underwent breast surgery until 2019 were included in the BRCA cohort. For each BRCA-carrier, three BRCA-noncarriers with HR-negative BC were matched based on age, time of diagnosis, and follow-up duration. Overall survival (OS) was analyzed using Kaplan‑Meier estimates and Cox proportional hazard ratios after adjustment for stage, chemotherapy, and surgical technique. A sensitivity analysis was performed to investigate the effect of HER2 status on HR-negative BC diagnosed after 2007. Results: Among the 106 BRCA carriers, 101 (95%) had a BRCA1 and 5 (5%) a BRCA2 PV. Most of the BRCA-carriers (89/106, 84%) were diagnosed with BC prior to genetic screening. Surgical techniques were similar between BRCA-carriers (n = 106) and noncarriers (n = 318). Chemotherapy was more common among BRCA-carriers (87% vs. 72%, p < 0.001). No significant difference in OS was found between BRCA-carriers and noncarriers among patients with HR-negative BC (adjusted HR: 0.81 [95% confidence interval [CI]: 0.43–1.53], p = 0.51) or considering HER2 status (adjusted HR 0.95 [95% CI: 0.43–2.07], p = 0.89). Interpretation: This study suggests that BRCA1/2 pathogenic variants do not independently impact survival outcomes in HR-negative BC. However, a moderate association between BRCA status and OS cannot be ruled out.

To evaluate the prognostic significance of changes in pre- and post-neoadjuvant chemotherapy (NACT) Ki67 in patients with primary invasive triple-negative breast cancer (TNBC). Population-based registry data were retrieved for patients diagnosed with TNBC between 2007 and 2021 (n = 9262). Multivariable Cox regression analysis was performed for disease-specific survival (DSS) and overall survival (OS) adjusted for age and residual disease in the breast and nodes (RDBN). Of the 1777 TNBC patients receiving NACT, 54 achieved pathologic complete response (pCR) and 755 had residual disease. Most patients were overweight with stage II disease (78

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors.

Lemur tail kinase 3 (LMTK3) belongs to a family of tyrosine kinases that are known to correlate with tumor grade and patient survival in some cancers. Here, we validated LMTK3 as a specific target and a prognostic biomarker in ovarian cancer (OC). In samples from 204 stage I-II OC patients, immunohistochemical studies revealed a higher cytoplasmic-to-nuclear staining intensity of LMTK3, which correlated with worse overall survival (p < 0.001). Efficacy studies utilizing novel LMTK3 binding peptides (LMTK3BPs) showed that all chemosensitive and chemoresistant OC cells were killed without affecting normal cells (p < 0.005), with synergistic effects shown following cisplatin and docetaxel treatment. In an orthotopic xenograft mouse model of OC, we saw a 35% tumor reduction in response to intravenous injections of 2 mg/kg LMTK3BP given three times a week for 3 weeks. Furthermore, in vivo safety studies showed no signs of toxicity after LMTK3BP treatment, even at doses as high as 40 mg/kg. This study highlights LMTK3 as a predictor of patient clinical outcomes. More importantly, novel LMTK3BPs represent potential safe treatment options, either alone or in combination with therapies, for OC.