Loss of progesterone receptor is associated with distinct tyrosine kinase profiles in breast cancer

A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer

PURPOSE

The impact of progesterone receptor (PR) status on the prognosis of breast cancer after isolated locoregional recurrence (ILRR) remains unclear. This study evaluated the impact of clinicopathologic factors, including PR status of ILRR, on distant metastasis (DM) after ILRR.

METHODS

We retrospectively identified 306 patients with ILRR diagnosed at the National Cancer Center Hospital between 1993 and 2021 from the database. Cox proportional hazards analysis was performed to examine factors associated with DM after ILRR. We developed a risk prediction model based on the number of detected risk factors and estimated survival curves using the Kaplan-Meier method.

RESULTS

During a median follow-up time of 4.7 years after ILRR diagnosis, 86 patients developed DM, and 50 died. Multivariate analysis revealed that seven risk factors were associated with poor distant metastasis-free survival (DMFS): estrogen receptor-positive/PR-negative/human epidermal growth factor receptor 2-negative ILRR, short disease-free interval, recurrence site other than ipsilateral breast, no-resection of ILRR tumor, chemotherapy for the primary tumor, nodal stage in the primary tumor, and no endocrine therapy for ILRR. The predictive model classified patients into 4 groups based on the number of risk factors: low-, intermediate-, high-, and the highest-risk groups with 0 to 1, 2, 3 to 4, and 5 to 7 factors, respectively. This revealed significant variation in DMFS among the groups. A higher number of the risk factors was associated with poorer DMFS.

CONCLUSION

Our prediction model, which considered the ILRR receptor status, may contribute to the development of a treatment strategy for ILRR.

Molecular Mechanisms of Anti-Estrogen Therapy Resistance and Novel Targeted Therapies

Breast cancer (BC) is the most commonly diagnosed cancer in women, constituting one-third of all cancers in women, and it is the second leading cause of cancer-related deaths in the United States. Anti-estrogen therapies, such as selective estrogen receptor modulators, significantly improve survival in estrogen receptor-positive (ER+) BC patients, which represents about 70% of cases. However, about 60% of patients inevitably experience intrinsic or acquired resistance to anti-estrogen therapies, representing a major clinical problem that leads to relapse, metastasis, and patient deaths. The resistance mechanisms involve mutations of the direct targets of anti-estrogen therapies, compensatory survival pathways, as well as alterations in the expression of non-coding RNAs (e.g., microRNA) that regulate the activity of survival and signaling pathways. Although cyclin-dependent kinase 4/6 and phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) inhibitors have significantly improved survival, the efficacy of these therapies alone and in combination with anti-estrogen therapy for advanced ER+ BC, are not curative in advanced and metastatic disease. Therefore, understanding the molecular mechanisms causing treatment resistance is critical for developing highly effective therapies and improving patient survival. This review focuses on the key mechanisms that contribute to anti-estrogen therapy resistance and potential new treatment strategies alone and in combination with anti-estrogen drugs to improve the survival of BC patients.

c-Kit Induces Migration of Triple-Negative Breast Cancer Cells and Is a Promising Target for Tyrosine Kinase Inhibitor Treatment

Triple-negative breast cancer (TNBC) is associated with a poor prognosis and the absence of targeted therapy. c-Kit, a receptor tyrosine kinase (RTK), is considered a molecular target for anticancer drugs. Tyrosine kinase inhibitors (TKIs) recognizing c-Kit are used for the treatment of c-Kit-expressing tumors. However, the expression, function, and therapeutic potential of c-Kit have been little explored in TNBC. Here, we studied the expression and effects of c-Kit in TNBC through in vitro and in silico analysis, and evaluated the response to TKIs targeting c-Kit. Analysis of TNBC cells showed the expression of functional c-Kit at the cell membrane. The stimulation of c-Kit with its ligand induced the activation of STAT3, Akt, and ERK1/2, increasing cell migration, but had no effect on cell proliferation or response to Doxorubicin. Analysis of public datasets showed that the expression of c-Kit in tumors was not associated with patient survival. Finally, TNBC cells were susceptible to TKIs, in particular the effect of Nilotinib was stronger than Doxorubicin in all cell lines. In conclusion, TNBC cells express functional c-Kit, which is a targetable molecule, and show a strong response to Nilotinib that may be considered a candidate drug for the treatment of TNBC.

Kinase activity profiling in renal cell carcinoma, benign renal tissue and in response to four different tyrosine kinase inhibitors

Kinase activity is frequently altered in renal cell carcinoma (RCC), and tyrosine kinase inhibitors (TKIs) are part of the standard treatment strategy in patients with metastatic disease. However, there are still no established biomarkers to predict clinical benefits of a specific TKI. Here, we performed protein tyrosine kinase (PTK) profiling using PamChip^® technology. The aim of this study was to identify differences in PTK activity between normal and malignant kidney tissue obtained from the same patient, and to investigate the inhibitory effects of TKIs frequently used in the clinics: sunitinib, pazopanib, cabozantinib and tivozanib. Briefly, our results showed that 36 kinase substrates differs (FDR < 0.05) between normal and cancer kidney tissue, where members of the Src family kinases and the phosphoinositide-3-kinase (PI3K) pathway exhibit high activity in renal cancer. Furthermore, ex vivo treatment of clear cell RCC with TKIs revealed that pathways such as Rap1, Ras and PI3K pathways were strongly inhibited, whereas the neurotrophin pathway had increased activity upon TKI addition. In our assay, tivozanib and cabozantinib exhibited greater inhibitory effects on PTK activity compared to sunitinib and pazopanib, implying they might be better suitable as TKIs for selected RCC patients.

Discovering biomarkers for hormone-dependent tumors: in silico study on signaling pathways implicated in cell cycle and cytoskeleton regulation

Malignancies dependent on hormone homeostasis include breast, ovary, cervical, prostate, testis and uterine tumors. Hormones are involved in signal transduction which orchestrate processes, such as apoptosis, proliferation, cell cycle or cytoskeleton organization. Currently, there is a need for novel biomarkers which would help to diagnose cancers efficiently. In this study, the genes implicated in signaling that is important in hormone-sensitive carcinogenesis were investigated regarding their prognostic significance. Data of seven cancer cohorts were collected from FireBrowse. 54 gene sets implicated in specific pathways were browsed through MSig database. Profiling was assessed via Monocle3, while gene ontology through PANTHER. For confirmation, correlation analysis was performed using WGCNA. Protein-protein networks were visualized via Cytoscape and impact of genes on survival, as well as cell cycle or cytoskeleton-related prognostic signatures, was tested. Several differences in expression profile were identified, some of them allowed to distinguish histology. Functional annotation revealed that various regulation of cell cycle, adhesion, migration, apoptosis and angiogenesis underlie these differences. Clinical traits, such as histological type or cancer staging, were found during evaluation of module-trait relationships. Of modules, the TopHubs (COL6A3, TNR, GTF2A1, NKX3-1) interacted directly with, e.g., PDGFB, ITGA10, SP1 or AKT3. Among TopHubs and interacting proteins, many showed an impact on hazard ratio and affected the cell cycle or cytoskeleton-related prognostic signatures, e.g., COL1A1 or PDGFB. In conclusion, this study laid the foundation for further hormone-sensitive carcinogenesis research through identification of genes which prove that crosstalk between cell cycle and cytoskeleton exists, opening avenues for future therapeutic strategies.

Molecular characterization of low-grade serous ovarian carcinoma identifies genomic aberrations according to hormone receptor expression

Hormone receptor expression is a characteristic of low-grade serous ovarian carcinoma (LGSOC). Studies investigating estrogen receptor (ER) and progesterone receptor (PR) expression levels suggest its prognostic and predictive significance, although their associations with key molecular aberrations are not well understood. As such, we sought to describe the specific genomic profiles associated with different ER/PR expression patterns and survival outcomes in a cohort of patients with advanced disease. The study comprised fifty-five advanced-staged (III/IV) LGSOCs from the Canadian Ovarian Experimental Unified Resource (COEUR) for which targeted mutation sequencing, copy-number aberration, clinical and follow-up data were available. ER, PR, and p16 expression were assessed by immunohistochemistry. Tumors were divided into low and high ER/PR expression groups based on Allred scoring. Copy number analysis revealed that PR-low tumors (Allred score <2) had a higher fraction of the genome altered by copy number changes compared to PR-high tumors (p = 0.001), with cancer genes affected within specific loci linked to altered peptidyl-tyrosine kinase, MAP-kinase, and PI3-kinase signaling. Cox regression analysis showed that ER-high (p = 0.02), PR-high (p = 0.03), stage III disease (p = 0.02), low residual disease burden (p = 0.01) and normal p16 expression (p<0.001) were all significantly associated with improved overall survival. This study provides evidence that genomic aberrations are linked to ER/PR expression in primary LGSOC.

The active kinome: The modern view of how active protein kinase networks fit in biological research

Biological regulatory networks are dynamic, intertwined, and complex systems making them challenging to study. While quantitative measurements of transcripts and proteins are key to investigate the state of a biological system, they do not inform the "active" state of regulatory networks. In consideration of that fact, "functional" proteomics assessments are needed to decipher active regulatory processes. Phosphorylation, a key post-translation modification, is a reversible regulatory mechanism that controls the functional state of proteins. Recent advancements of high-throughput protein kinase activity profiling platforms allow for a broad assessment of protein kinase networks in complex biological systems. In conjunction with sophisticated computational modeling techniques, these profiling platforms provide datasets that inform the active state of regulatory systems in disease models and highlight potential drug targets. Taken together, system-wide profiling of protein kinase activity has become a critical component of modern molecular biology research and presents a promising avenue for drug discovery.

Lost but Not Least-Novel Insights into Progesterone Receptor Loss in Estrogen Receptor-Positive Breast Cancer

Estrogen receptor α (ERα) and progesterone receptor (PgR) are crucial prognostic and predictive biomarkers that are usually co-expressed in breast cancer (BC). However, 12-24% of BCs present ERα(+)/PgR(-) phenotype at immunohistochemical evaluation. In fact, BC may either show primary PgR(-) status (in chemonaïve tumor sample), lose PgR expression during neoadjuvant treatment, or acquire PgR(-) phenotype in local relapse or metastasis. The loss of PgR expression in ERα(+) breast cancer may signify resistance to endocrine therapy and poorer outcomes. On the other hand, ERα(+)/PgR(-) BCs may have a better response to neoadjuvant chemotherapy than double-positive tumors. Loss of PgR expression may be a result of pre-transcriptional alterations (copy number loss, mutation, epigenetic modifications), decreased transcription of the PGR gene (e.g., by microRNAs), and post-translational modifications (e.g., phosphorylation, sumoylation). Various processes involved in the down-regulation of PgR have distinct consequences on the biology of cancer cells. Occasionally, negative PgR status detected by immunohistochemical analysis is paradoxically associated with enhanced transcriptional activity of PgR that might be inhibited by antiprogestin treatment. Identification of the mechanism of PgR loss in each patient seems challenging, yet it may provide important information on the biology of the tumor and predict its responsiveness to the therapy.