Breast Cancer Plasticity after Chemotherapy Highlights the Need for Re-Evaluation of Subtyping in Residual Cancer and Metastatic Tissues.

This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes). Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC. Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data. Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals.

A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer.

BACKGROUND: Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors. METHODS: Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively. RESULTS: A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression ("Stromal-UP" (SU) and "Stromal-DOWN" (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival. CONCLUSIONS: A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.

Epithelial-to-Mesenchymal Transition Is Not a Major Modulating Factor in the Cytotoxic Response to Natural Products in Cancer Cell Lines.

Numerous natural products exhibit antiproliferative activity against cancer cells by modulating various biological pathways. In this study, we investigated the potential use of eight natural compounds (apigenin, curcumin, epigallocatechin gallate, fisetin, forskolin, procyanidin B2, resveratrol, urolithin A) and two repurposed agents (fulvestrant and metformin) as chemotherapy enhancers and mesenchymal-to-epithelial (MET) inducers of cancer cells. Screening of these compounds in various colon, breast, and pancreatic cancer cell lines revealed anti-cancer activity for all compounds, with curcumin being the most effective among these in all cell lines. Although some of the natural products were able to induce MET in some cancer cell lines, the MET induction was not related to increased synergy with either 5-FU, irinotecan, gemcitabine, or gefitinib. When synergy was observed, for example with curcumin and irinotecan, this was unrelated to MET induction, as assessed by changes in E-cadherin and vimentin expression. Our results show that MET induction is compound and cell line specific, and that MET is not necessarily related to enhanced chemosensitivity.

Renin angiotensin system genes are biomarkers for personalized treatment of acute myeloid leukemia with Doxorubicin as well as etoposide.

Despite the availability of various treatment protocols, response to therapy in patients with Acute Myeloid Leukemia (AML) remains largely unpredictable. Transcriptomic profiling studies have thus far revealed the presence of molecular subtypes of AML that are not accounted for by standard clinical parameters or by routinely used biomarkers. Such molecular subtypes of AML are predicted to vary in response to chemotherapy or targeted therapy. The Renin-Angiotensin System (RAS) is an important group of proteins that play a critical role in regulating blood pressure, vascular resistance and fluid/electrolyte balance. RAS pathway genes are also known to be present locally in tissues such as the bone marrow, where they play an important role in leukemic hematopoiesis. In this study, we asked if the RAS genes could be utilized to predict drug responses in patients with AML. We show that the combined in silico analysis of up to five RAS genes can reliably predict sensitivity to Doxorubicin as well as Etoposide in AML. The same genes could also predict sensitivity to Doxorubicin when tested in vitro. Additionally, gene set enrichment analysis revealed enrichment of TNF-alpha and type-I IFN response genes among sensitive, and TGF-beta and fibronectin related genes in resistant cancer cells. However, this does not seem to reflect an epithelial to mesenchymal transition per se. We also identified that RAS genes can stratify patients with AML into subtypes with distinct prognosis. Together, our results demonstrate that genes present in RAS are biomarkers for drug sensitivity and the prognostication of AML.

Predictive Gene Signature for Pyrazolopyrimidine Derivative c-Src Inhibitor 10a Sensitivity in Melanoma Cells.

Melanoma is a highly aggressive cancer with poor prognosis. Although more than 80% of melanomas harbor an activating mutation in genes within the MAPK pathway, which are mutually exclusive, usefulness of therapies targeting MAPK pathway are impeded by innate and/or acquired resistance in most patients. In this study, using melanoma cells, we report the efficacy of a recently developed pyrazolo[3,4-d]pyrimidine derived c-Src inhibitor 10a and identify a molecular signature which is predictive of 10a chemosensitivity. We show that the expression of TMED7, PLOD2, XRCC5, and NSUN5 are candidate biomarkers for 10a sensitivity. Although an undifferentiated/mesenchymal/invasive status of melanoma cells is associated with resistance to 10a, we show here for the first time that melanoma cells can be sensitized to 10a via treatment with valproic acid, a histone deacetylase inhibitor.

A novel 20-gene prognostic score in pancreatic adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Known risk factors for this disease are currently insufficient in predicting mortality. In order to better prognosticate patients with PDAC, we identified 20 genes by utilizing publically available high-throughput transcriptomic data from GEO, TCGA and ICGC which are associated with overall survival and event-free survival. A score generated based on the expression matrix of these genes was validated in two independent cohorts. We find that this "Pancreatic cancer prognostic score 20 -PPS20" is independent of the confounding factors in multivariate analyses, is dramatically elevated in metastatic tissue compared to primary tumor, and is higher in primary tumors compared to normal pancreatic tissue. Transcriptomic analyses show that tumors with low PPS20 have overall more immune cell infiltration and a higher CD8 T cell/Treg ratio when compared to those with high PPS20. Analyses of proteomic data from TCGA PAAD indicated higher levels of Cyclin B1, RAD51, EGFR and a lower E-cadherin/Fibronectin ratio in tumors with high PPS20. The PPS20 score defines not only prognostic and biological sub-groups but can predict response to targeted therapy as well. Overall, PPS20 is a stronger and more robust transcriptomic signature when compared to similar, previously published gene lists.

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer.

Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

Simultaneous miRNA and mRNA transcriptome profiling of glioblastoma samples reveals a novel set of OncomiR candidates and their target genes.

Although glioblastomas are common, there remains a need to elucidate the underlying mechanisms behind their initiation and progression and identify molecular pathways for improving treatment. In this study, sixteen fresh-frozen glioblastoma samples and seven samples of healthy brain tissues were analyzed with miRNA and whole transcriptome microarray chips. Candidate miRNAs and mRNAs were selected to validate expression in fifty patient samples in total with the criteria of abundance, relevance and prediction scores. miRNA and target mRNA relationships were assessed by inhibiting selected miRNAs in glioblastoma cells. Functional tests have been conducted in order to see the effects of miRNAs on invasion, migration and apoptosis of GBM cells. Analyses were carried out to determine correlations between selected molecules and clinicopathological features. 1332 genes and 319 miRNAs were found to be dysregulated by the microarrays. The results were combined and analyzed with Transcriptome Analysis Console 3 software and the DAVID online database. Primary differential pathways included Ras, HIF-1, MAPK signaling and cell adhesion. OncomiR candidates 21-5p, 92b-3p, 182-5p and 339-5p for glioblastoma negatively correlated with notable mRNA targets both in tissues and in in vitro experiments. miR-21-5p and miR-339-5p significantly affected migration, invasion and apoptosis of GBM cells in vitro. Significant correlations with overall survival, tumor volume, recurrence and age at diagnosis were discovered. In this article we present valuable integrated microarray analysis of glioblastoma samples regarding miRNA and gene-expression levels. Notable biomarkers and miRNA-mRNA interactions have been identified, some of which correlated with clinicopathological features in our cohort.

Epigenetic mechanisms underlying the dynamic expression of cancer-testis genes, PAGE2, -2B and SPANX-B, during mesenchymal-to-epithelial transition.

Cancer-testis (CT) genes are expressed in various cancers but not in normal tissues other than in cells of the germline. Although DNA demethylation of promoter-proximal CpGs of CT genes is linked to their expression in cancer, the mechanisms leading to demethylation are unknown. To elucidate such mechanisms we chose to study the Caco-2 colorectal cancer cell line during the course of its spontaneous differentiation in vitro, as we found CT genes, in particular PAGE2, -2B and SPANX-B, to be up-regulated during this process. Differentiation of these cells resulted in a mesenchymal-to-epithelial transition (MET) as evidenced by the gain of epithelial markers CDX2, Claudin-4 and E-cadherin, and a concomitant loss of mesenchymal markers Vimentin, Fibronectin-1 and Transgelin. PAGE2 and SPAN-X up-regulation was accompanied by an increase in Ten-eleven translocation-2 (TET2) expression and cytosine 5-hydroxymethylation as well as the disassociation of heterochromatin protein 1 and the polycomb repressive complex 2 protein EZH2 from promoter-proximal regions of these genes. Reversal of differentiation resulted in down-regulation of PAGE2, -2B and SPANX-B, and induction of epithelial-to-mesenchymal transition (EMT) markers, demonstrating the dynamic nature of CT gene regulation in this model.