Low-grade serous ovarian carcinoma (LGSOC) is a rare, indolent ovarian cancer subtype with limited effective therapies. Approximately 40% of cases lack canonical MAPK/ERK or PI3K/AKT/mTOR pathway alterations and are classified as having no specific molecular profile (NSMP). These patients have poor responses to chemotherapy, MEK inhibitors, and hormonal therapies, highlighting the need for alternative strategies. This study aimed to identify novel therapeutic targets in NSMP LGSOC. A high-throughput drug screen of 3,436 compounds (including FDA-approved, clinically tested, and investigational agents) was conducted across 12 LGSOC and one control ovarian epithelial cell line. EGFR inhibitors emerged as selective hits in NSMP cell lines and were further tested in two NSMP and two MAPK-mutant lines in combination with standard-of-care chemotherapy agents, carboplatin and paclitaxel. EGFR expression was assessed using RNA sequencing, DNA methylation profiling, and immunohistochemistry in primary tumors, followed by survival analysis based on expression levels. Unsupervised clustering of drug response data revealed subtype-specific vulnerabilities, with EGFR inhibitors showing marked cytotoxicity in all five NSMP lines (robust Z-score ≤ -2), and minimal activity in MAPK- and USP9X-mutant lines. EGFR inhibitors (avitinib, AV-412) showed selective, low-dose synergy with standard-of-care chemotherapy in NSMP models, with minimal and inconsistent effects in MAPK-mutant lines. NSMP tumors showed elevated EGFR mRNA and EGFR protein expression, associated with poor survival, advanced disease stage, and peritoneal involvement, and inversely correlated with MAPK mutations. These findings position EGFR overexpression as a defining and targetable feature of NSMP LGSOC and support further preclinical validation of EGFR inhibitors as a treatment strategy for this understudied cancer subtype. © 2026 The Pathological Society of Great Britain and Ireland.

Modern biology increasingly relies on large-scale screening to generate high dimensional datasets with potential to accelerate discovery. However, analysing these complex datasets remains challenging, due to hierarchical biological structure, uncertainty in the true number of groups, and high dimensional noise that confounds genuine biological signal. Here we present an unsupervised consensus clustering tool, Untangled, that aggregates clustering solutions across granularities to construct a stability-based representation, followed by cluster number optimization and systematic evaluation of cluster robustness. Through extensive benchmarking on simulated datasets, ground truth datasets and diverse high-dimensional screening applications, we demonstrate that Untangled reliably recovers underlying relationships, resolves stable meaningful substructure, and more effectively prioritizes robust clusters with shared biological mechanisms and conserved phenotypic responses than alternative clustering approaches. These results establish Untangled as a scalable framework for cluster discovery to guide efficient follow-up investigation from high-dimensional biological datasets.

Epidemiological studies have shown that high mammographic density (HMD) is a strong risk factor for breast cancer (BC) and is associated with poor prognosis. Although tumors from women with low (LMD) and HMD are genetically similar, HMD has a worse prognosis. We explored whether differences in the immune tumor microenvironment could explain the poorer outcomes. BC data were predominantly obtained from Lifepool, a population-based cohort of over 55,000 Australian women within the screening program. We identified 670 cases of invasive BC with pathology reports, family cancer history, and matched MD data to evaluate the clinico-pathological features of BC across MD quintiles. Tumour tissue was retrieved from 122 cases and we performed multiplexed immunohistochemistry to assess the infiltration of immune cells. Whole-genome sequencing (WGS) was performed on twelve luminal BCs of ductal origin, which included 4 LMD, and 5 HMD cases. Additional cases for WGS were obtained from the MAGIC study. BCs in women with HMD were linked to older age at diagnosis, higher rates of interval cancers, distinct histological subtypes, and a stronger family history of BC. Mutational signatures showed increased homologous recombination deficiency. APOBEC-associated mutations were unique to LMD. HMD also exhibited a significant rise in adaptive immune cells, including T cell B cells. Our findings suggest that HMD is associated with distinct somatic genetic events and an immune microenvironment that favors tumor-promoting immune cells within BC.

Low-grade serous ovarian carcinoma (LGSOC) usually presents in advanced stages and is associated with a high mortality rate. Clinical trials targeting the MAPK and cell cycle pathways in LGSOC have shown promising results for its treatment, however there is a need to improve efficacy and define predictive biomarkers to guide patient selection for treatment using these agents. We therefore evaluated cell cycle protein expression by immunohistochemistry (IHC) in 186 LGSOC cases, and evaluated the efficacy of the MEK inhibitor, trametinib, in combination with the CDK4/6 inhibitor, palbociclib, in preclinical models of LGSOC. Abnormal p16 expression was observed in 20% of primary and 46% of recurrent tumors, and it was associated with poorer survival (log-rank p = 0.005). Notably, cell lines with increased sensitivity to trametinib were more likely to harbor mutations in KRAS or NF1 and displayed low pRb levels. Palbociclib showed limited efficacy in vitro; however, the combination of palbociclib and trametinib treatment produced synergistic antiproliferative effects in KRAS/NF1-wild-type cell lines, which displayed higher pRb levels. Acquired drug resistance was linked to increased cyclin D1/E1 expression. This study confirms abnormal p16 IHC as a negative prognostic marker in LGSOC and establishes key determinants of sensitivity to CDK4/6 inhibitor-based therapy.

Schema of study numbers for each analysis to describe different cohort numbers due to pathology review and missing data. MOC, mucinous ovarian carcinoma; MBOT, mucinous borderline ovarian tumor; LGI, lower gastrointestinal; UGI, upper gastrointestinal; SISH, silver in situ hybridization.

Associations between gene expression and stage group and OS in MOC.

Kaplan–Meier curves of OS in (A) main tumor groups (n = 582)—MBOT, MOC, LGI, and UGI; (B) patients with MOC by FIGO stage (n = 184); (C) patients with MOC by pattern of invasion in all stages (n = 178); and (D) patients with stage I MOC (n = 134), by pattern of invasion.

High-grade serous ovarian carcinoma (HGSOC) has a significant hereditary component, only half of which is explained. Previously, we performed germline exome sequencing on BRCA1 and BRCA2-negative HGSOC patients, revealing three proposed and 43 novel candidate genes enriched with rare loss-of-function variants. For validation, we undertook case-control analyses using genomic data from disease-free controls. This confirms enrichment for nearly all previously identified genes. Additionally, one-hundred-and-eleven HGSOC tumours from variant carriers were sequenced alongside other complementary studies, seeking evidence of biallelic inactivation as supportive evidence. PALB2 and ATM validate as HGSOC predisposition genes, with 6/8 germline carrier tumours exhibiting biallelic inactivation accompanied by characteristic mutational signatures. Among candidate genes, only LLGL2 consistently shows biallelic inactivation and protein expression loss, supporting it as a novel HGSOC susceptibility gene. The remaining candidate genes fail to validate. Integrating case-control analyses with tumour sequencing is thus crucial for accurate gene discovery in familial cancer studies.

Heat map of unsupervised clustering analysis. Contains all samples with a concordant pathology diagnosis (n = 497), with MOC grouped by FIGO stage. Labels show main clusters and diagnoses. Gene-expression values are normalized and logarithm base 2 transformed. dx, diagnosis.

Supplementary Figures S1-S13

Overall survival in MOC by pattern of invasion.

Supplementary Tables S1-S11

Patient characteristics and analytical cohorts.

Low-grade serous carcinoma (LGSC) is an uncommon histotype of ovarian carcinoma, accounting for ~3% of cases. There is evidence that survival of peritoneal LGSC (pLGSC) is longer than that of ovarian LGSC (oLGSC). Key molecular alterations of LGSC have been established, including loss of CDKN2A and PR expression, MAPK pathway alterations, and loss of USP9X expression. We hypothesized that LGSC could be subclassified into clinically applicable molecular subtypes by a few surrogate tests similar to endometrioid carcinomas using a hierarchical decision tree based on the strength of the prognostic associations of the individual alterations. Our study included 71 LGSCs. Immunohistochemistry for CDKN2A, ER, PR, NF1, and USP9X and sequencing for KRAS, NRAS, and BRAF were performed. Our data showed the co-occurrence of key molecular alterations, and despite suggestive trends, hierarchical molecular subtyping did not provide significantly different stratification of patients according to survival in this cohort. We confirmed that patients diagnosed with pLGSC have a longer survival than high-stage oLGSC, with the intriguing observation that normal CDKN2A and PR status were associated with excellent survival in pLGSC. Therefore, CDKN2A and PR status might aid in the classification of indeterminate implants, where abnormal findings favor pLGSC over noninvasive implants. Molecular subtypes should be further evaluated in larger cohorts for their prognostic and potentially predictive value.

Abstract Low grade serous carcinoma (LGSOC) is a rare epithelial ovarian cancer with unique molecular characteristics compared to the more common tubo-ovarian high-grade serous ovarian carcinoma. Pivotal clinical trials guiding the management of epithelial ovarian cancer lack sufficient cases of LGSOC for meaningful subgroup analysis, hence overall findings cannot be extrapolated to rarer chemo-resistant subtypes such as LGSOC. Furthermore, there is a need for more effective therapies for the treatment of relapsed disease, as treatment options are limited. To address this, we conducted the largest quantitative high-throughput drug screening effort (n = 3436 compounds) in 12 patient-derived LGSOC cell lines and one normal ovary cell line to identify unexplored therapeutic avenues. Using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines, our data set identified 60 high and 19 moderate confidence hits which induced cancer cell specific cytotoxicity at the lowest compound dose assessed (0.1 µM). We also revealed a series of known (mTOR/PI3K/AKT) and novel (EGFR and MDM2-p53) drug classes in which LGSOC cell lines showed demonstrable susceptibility to.

High-throughput analysis methods have emerged as central technologies to accelerate discovery by accelerating generation of large-scale data. Analysis and interpretation of these datasets remains challenging due to limitations in computational approaches for dimensionality reduction. Here, we present UnTANGLeD, a versatile computational pipeline that prioritises biologically robust and meaningful information to guide actionable strategies from input screening data which we demonstrate using results from image-based drug screening. By providing a robust framework for analysing high dimensional biological data, UnTANGLeD offers a powerful tool for analysis of theoretically any data type from any screening platform. ### Competing Interest Statement The authors have declared no competing interest.

Abstract MYB oncogene upregulation is associated with estrogen receptor (ER)-positive breast cancer, but disease requirements for MYB function in vivo have not been explored. In this study, we provide evidence of a critical requirement for MYB functions in models of human and murine breast cancer. In human breast cancer, we found that MYB expression was critical for tumor cell growth both in vitro and in vivo in xenograft settings. In transgenic knockout mice, tissue-specific deletion of the murine MYB gene caused a transient defect in mammary gland development that was reflected in delayed ductal branching and defective apical bud formation. In mouse mammary tumor virus (MMTV)-NEU mice where tumors are initiated by activation of HER2, MYB deletion was sufficient to abolish tumor formation. In the more aggressive MMTV-PyMT model system, MYB deletion delayed tumorigenesis significantly. Together, the findings in these transgenic knockout models implied that MYB was critical during an early window in mammary development when it was essential for tumor initiation, even though MYB loss did not exert a lasting impact upon normal mammary function. Two important MYB-target genes that promote cell survival, BCL2 and GRP78/BIP, were each elevated compared with nontransformed mammary epithelial cells, thereby promoting survival as confirmed in colony formation assays in vitro. Taken together, our findings establish a role for MYB at the hub of ER- and HER2-dependent pathways in mammary carcinogenesis. Cancer Res; 71(22); 7029–37. ©2011 AACR.

PDF file - 998K, Extent of proliferation, MYB and ER expression in wt virgin mammary glands.

PDF file - 89K, Epithelial cell gene expression in tissues employed for the analysis of MYB and A-MYB expression in mammary glands at different stages of development contain epithelial cells.