TEST:

Prosigna™ Breast Cancer Prognostic Gene Signature Assay

This analysis suggests that the Decipher genomic classifier may be prognostic for disease progression in AS patients with low- to intermediate-risk prostate cancer. Higher Decipher and AR-A scores, as well as PAM50 luminal subtypes, may also serve as biomarkers for treatment response.

In addition, it has been determined that these molecules can be useful in the classification of BC, especially in determining the basal-like breast cancer (BLBC) subtype. We conclude that hsa_circ_0000515/miR-486-5p/SDC1 axis may be an important biomarker candidate in distinguishing patients in the BLBC subgroup of BC.

P2, N=73, Completed, SOLTI Breast Cancer Research Group | Active, not recruiting --> Completed

P2, N=46, Active, not recruiting, SOLTI Breast Cancer Research Group | Trial completion date: Nov 2024 --> May 2024 | Trial primary completion date: Dec 2023 --> Apr 2024

P2, N=55, Recruiting, SOLTI Breast Cancer Research Group | Trial primary completion date: Dec 2023 --> Dec 2024

P=N/A, N=60, Active, not recruiting, Dana-Farber Cancer Institute | Recruiting --> Active, not recruiting | Trial completion date: Jan 2024 --> Dec 2024

P1/2, N=116, Recruiting, Cantargia AB | Phase classification: P1b/2 --> P1/2

Synergies between MELK inhibition with 4OH-tamoxifen (Tam) and ALK inhibition with HER2 inhibitors revealed potential therapeutic avenues for ERα-positive/PR-positive/HER2-negative and ERα-positive/PR-negative/HER2-positive tumors, respectively. Our findings propose MELK as a promising target for ERα-positive/PR-positive/HER2-negative BC and highlight ALK as a potential focus for ERα-positive/PR-negative/HER2-positive BC. The synergistic anti-proliferative effects of MELK with Tam and ALK with HER2 inhibitors underscore kinase inhibitors' potential for selective treatment in diverse BC subtypes, paving the way for personalized and effective therapeutic strategies in BC management.

Discordance occurred more often among patients with N3, stage IV, or grade III disease.CONCLUSIONOur findings indicate that molecular subtypes are a predominant classification for survival. Assessment is particularly crucial for patients with IHC luminal breast cancer with known high-risk factors, since they are at an increased risk of harboring an aggressive molecular subtype.

The results from this clinical evaluation of image-based risk stratification shows a considerable agreement to an established gene expression assay in routine breast pathology.

P=N/A, N=1167, Recruiting, Breast Cancer Trials, Australia and New Zealand | Phase classification: P3 --> P=N/A | Trial completion date: Dec 2023 --> Apr 2026 | Trial primary completion date: Dec 2023 --> Oct 2025

P2; These results highlight the clinical, biological, and metabolic heterogeneity of HER2+ breast cancer, which may facilitate the selection of HER2+ EBC patients likely to benefit from [18F]FDG-PET imaging as a tool to guide therapy.

In the context of generating supervised machine learning classifiers for molecular subtypes, FSQN and FSMVN are equally effective. Under optimal modeling conditions, FSQN and FSMVN provide equivalent model accuracy performance on cross-platform normalization data compared to within-platform data. Using cross-platform data should still be approached with caution as subtle performance differences may exist depending on the classification problem, training, and testing distributions.

Patients with nonpalpable breast cancer found at screening with negative nodes are at very low risk. It is possible to identify subgroups without metastatic events by determining the intrinsic subtype and tumor size less than 1 cm. Therefore, de-escalation of treatment should be considered.

Black and younger women with breast cancer have a higher burden of BIRC5-high tumors than older and non-Black women. Emerging anti-survivin treatment strategies may be an important future direction for equitable breast cancer outcomes.

Our research reveals the clinical significance of CADM3 in BC and indicates the critical roles of CADM3 in immune infiltration and MAPK pathway.

ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

No abstract available

When applied to breast cancer histology and RNA-sequencing expression data from The Cancer Genome Atlas (TCGA), our model can provide survival predictions with average concordance-indices of up to 68.32% along with interpretability. We also illustrate how the pCCA embeddings can be used for survival analysis through Kaplan-Meier curves.

P1/2; N=204 --> 24 | Trial completion date: Nov 2024 --> Mar 2025 | Trial primary completion date: Nov 2024 --> Jun 2023

P2; N=87 --> 0 | Not yet recruiting --> Withdrawn

We found that gene signatures provide prognostic information in survival analyses of all, ER + /LN + and ER + /LN- older (≥ 70 years) breast cancer patients, suggesting a potential role in aiding treatment decisions in older patients.

We examined common prostate cancer tumor subtypes and found marked heterogeneity across PIRADS lesions, with some variation between tumors from AA vs. non-AA. Our study not only highlights the correlation between tumor biology and MRI images, but it also raises the question of whether the biological differences in PCa between AA and non-AA are reflected differently on mpMRI, and if that means we should interpret these diagnostic studies differently in diverse populations.

Despite similar clinical features at diagnosis, AS-eligible patients have significantly different outcomes and risk of APF due to molecular heterogeneity. The Decipher genomic classifier, PTEN loss, and activated CD4 activity at diagnosis are associated with APF among AS eligible patients. Clinical trials within AS populations should consider utility of genomic signatures in patient selection.

Higher GLP1R gene expression was associated with basal subtype prostate cancer, lower AR activity and a more suppressed tumor immune microenvironment while higher GCG gene expression was associated with lower Gleason grade group and NCCN low risk tumors. This study lays the groundwork for clinical investigation of potential use of GLP1R agonists in the management of different facets of prostate cancer.

P2; Trial completion date: Dec 2031 --> Apr 2032 | Trial primary completion date: Jun 2026 --> Apr 2027

Our transcriptomic approach emphasize a molecular phenotype of B-cell immunity in ER+ BC that may help to predict disease prognosis. Although further researches are required, B-cell immunity for patients with ER+ BC may be helpful for identifying patients who are good responders to chemotherapy or immunotherapy.

P=N/A; GEX of AR adds prognostic information for MBC. Our descriptive analyses illuminate the biological differences between MBCs in relation to outcome and metastatic site.

Immunologically, ribociclib was associated with downregulated GES associated with APCs and the innate immune system in Luminal B tumors, contrary to existing preclinical data. Further studies are needed to understand the effect of CDK4/6 inhibition on the tumor cells and microenvironment, an effect which may vary according to tumor subtypes.

The identified gene subsets, with 36 genes, have the potential to contribute to the development of more cost-effective and streamlined diagnostic tools in breast cancer research and clinical settings.

P2; Trial primary completion date: Feb 2024 --> Dec 2024

Lastly, we identified RTN1 as a potential biomarker, exhibiting lower expression in sensitive rare-tumor PDX models prior to Axitinib and Vandetanib treatment.ConclusionsWith the multi-omics datasets comprising proteomics/phospho-proteomics, RNA-Seq and WES datasets from the NCI Patient Derived Models Repository cohort, we were able to query some important cancer biological processes at a higher resolution. In addition, we revealed gene- and pathway-level regulatory differences from various histologies. Overall, the multi-omics data from PDX models showed promising recapitulation of original tumor activity and should continue to serve as an amenable and scalable drug screening platform for pre-clinical trials.

Funded by NCI Contract No. HHSN261200800001E

We are the first study to profile immune microenvironment using both transcriptomic and IHC methods. Our study is also unique in using NPBC and BC>2Y patients as control groups for PABC patients. CD8+ T cells are statistically higher in PABC patients than in NPBC patients using either transcriptomic profiling or multiplex IHC analysis.

The top five most important features contributing to the random forest model were Sulfidibacter, Prestia, Cutibacterium, Acinetobacter and Rhizobium. This study is the largest to date that characterize the tumor microbiota of an Asian cohort of breast cancers, where Sulfidibacter and Priestia, both relatively new and uncharacterized bacteria, were differentially abundant among patients with high vs low immune scores.

In summary, DeepHRD exhibits consistent hazard ratios ranging from 0.45 to 0.49 across the three clinical cohorts and captures 1.8- to 3.1-fold more HRD-positive breast and ovarian cancer patients. DeepHRD-positive breast cancer patients that received platinum exhibited better complete response and PFS. Similarly, DeepHRD-positive platinum-treated ovarian cancer patients had a better OS.

Our findings show that AAW with HR+ breast cancer have tumors with more inherently aggressive molecular subtypes associated with poor prognosis compared to EAW. These results also further support the premise that HR+/HER2- tumors are highly heterogeneous and strongly suggest that chemokine gene expression is associated with breast cancer subtype.

We have previously found that loss of MYH9 sensitizes to the HER family inhibitor neratinib treatment as assessed by cell proliferation, colony formation on matrigel, cell migration and invasion...Given our identification of NMIIA as one of the interacting partners of HER3, our focus will be on investigating the NMIIA-HER3 signaling axis to elucidate its contribution to an adaptive response to HER2 inhibition and potential treatment resistance. Furthermore, we will explore strategies to target NMIIA in breast cancer.

We find that core microenvironment context directly influences diagnostic accuracy. Maximizing tumor content improves diagnostic accuracy on the PAM50 task, with the majority cancerous TMAs obtaining an AUROC of 0.80 (95% confidence interval 0.75-0.85), relative to 0.72 (95% CI 0.66-0.78) for majority non-cancerous TMAs and 0.82 (95% CI 0.80-0.84) for WTS images.Notably, our context-aware TMA sampling achieves accuracy within 2% of the WTS images, while poorly selected TMA cores underperform the WTS baseline by 10% on average. While TCGA is curated to contain patients with a very high tumor burden, and consequently random TMA selection performs well on this cohort (AUROC 0.77; 95% CI 0.74-0.79), our study indicates that tissue context is an important consideration when selecting cores from real donor tissue blocks.Our results demonstrate that TMA core sampling protocols should be informed by TME context to maximize analysis accuracy, and that intelligent core sampling can largely close the gap to WTS image accuracies on clinically-relevant tasks like PAM50 subtype prediction.

Our flexible analytic framework for reconstructing gene expression profiles from clinicogenomics data substantially augments the clinical utility and value of data acquired in real-world settings.

This study expands on previous findings by demonstrating that BCAR4 expression is associated with resistance to newer therapies. The identification of patients with intrinsic resistance to hormone therapy is crucial to avoid ineffective treatment strategies. These findings contribute to our understanding of endocrine therapy resistance in breast cancer and could potentially guide the development of more effective treatment strategies.

P3; Trial completion date: Dec 2027 --> Mar 2028