Deep learning transcriptomic model for prediction of pan-drug chemotherapeutic sensitivity

The emergence of precision oncology approaches has begun to inform clinical decision-making in diagnostic, prognostic, and treatment contexts. High-throughput technology has enabled machine learning algorithms to use the molecular characteristics of tumors to generate personalized therapies. However, precision oncology studies have yet to develop a predictive biomarker incorporating pan-cancer gene expression profiles to stratify tumors into similar drug sensitivity profiles. Here we show that a neural network with ten hidden layers accurately classifies pancancer cell lines into two distinct chemotherapeutic response groups based on a pan-drug dataset with 89.0% accuracy (AUC = 0.904). Using unsupervised clustering algorithms, we found a cohort of cell line gene expression data from the Genomics of Drug Sensitivity in Cancer could be clustered into two response groups with significant differences in pan-drug chemotherapeutic sensitivity. After applying the Boruta feature selection algorithm to this dataset, a deep learning model was developed to predict chemotherapeutic response groups. The model’s high classification efficacy validates our hypothesis that cell lines with similar gene expression profiles present similar pan-drug chemotherapeutic sensitivity. This finding provides evidence for the potential use of similar combinatorial biomarkers to select potent candidate drugs that maximize therapeutic response and minimize the cytotoxic burden. Future investigations should aim to recursively subcluster cell lines within the response clusters defined in this study to provide a higher resolution of potential patient response to chemotherapeutics.

Menin inhibition suppresses castration-resistant prostate cancer and enhances chemosensitivity

Disease progression and therapeutic resistance of prostate cancer (PC) are linked to multiple molecular events that promote survival and plasticity. We previously showed that heat shock protein 27 (HSP27) acted as a driver of castration-resistant phenotype (CRPC) and developed an oligonucleotides antisense (ASO) against HSP27 with evidence of anti-cancer activity in men with CRPC. Here, we show that the tumor suppressor Menin (MEN1) is highly regulated by HSP27. Menin is overexpressed in high-grade PC and CRPC. High MEN1 mRNA expression is associated with decreased biochemical relapse-free and overall survival. Silencing Menin with ASO technology inhibits CRPC cell proliferation, tumor growth, and restores chemotherapeutic sensitivity. ChIP-seq analysis revealed differential DNA binding sites of Menin in various prostatic cells, suggesting a switch from tumor suppressor to oncogenic functions in CRPC. These data support the evaluation of ASO against Menin for CRPC.

RNA-binding proteins modulate drug sensitivity of cancer cells

As our understanding of the complex network of regulatory pathways for gene expression continues to grow, avenues of investigation for how these new findings can be utilised in therapeutics are emerging. The recent growth of interest in the RNA binding protein (RBP) interactome has revealed it to be rich in targets linked to, and causative of diseases. While this is, in and of itself, very interesting, evidence is also beginning to arise for how the RBP interactome can act to modulate the response of diseases to existing therapeutic treatments, especially in cancers. Here we highlight this topic, providing examples of work that exemplifies such modulation of chemotherapeutic sensitivity.

Clinical Implication of N6-Methylandenosine-Related lncRNAs in Non-Small Cell Lung Cancer

Background: Non-small-cell lung cancer (NSCLC) represents the leading cause of cancer-related deaths worldwide and is highly heterogeneous. The N6-methyladenosine (m6A) RNA, a vital contributor to the outcomes of cancer, can modify long non-coding RNAs (lncRNAs), thereby influencing the transcript stability, gene expression, and serving a wide array of biological functions. However, the role of m6A-related lncRNAs in NSCLC remains largely unknown. Methods: We identified a group of m6A-related lncRNAs (m6ARLncRNAs) by using co-expression analysis in 1835 NSCLC patients from The Cancer Genome Atlas (TCGA) (N=1145) and Gene Expression Omnibus (GEO) (N=690) datasets. We employed consensus unsupervised clustering analysis to explore molecular patterns based on the expression of m6ARLncRNAs. Then we filtered m6ARLncRNAs by Cox regression and LASSO regression to construct a m6ARLncRNAs signature (m6ARLncSig) and further evaluated m6ARLncSig with external and experimental validation by using qRT-PCR. We analyzed the correlation between m6ARLncSig scores groups with clinical features, chemotherapeutic sensitivity and radiotherapeutic response. Finally, we established a nomogram for prognosis prediction in patients with LUAD and validated it in the testing set and the entire TCGA dataset. Results: We constructed a m6ARLncSig for prognosis prediction of patients consisting of 12 m6ARLncRNAs. The m6ARLncSig divided patients into a high-risk group and a low-risk one, which had significantly different OS and could independently predict the prognosis of patients. Meanwhile, we revealed that patients in the high- and low-risk groups differed in tumor-infiltrating immune cells, and chemotherapeutic sensitivity, and biological pathways. Of note, we found that m6ARLncSig was associated with age, tumor stage, and radiotherapeutic response, indicating they were clinically relevant. Conclusions: Our study demonstrated that m6ARLncSig could act as a potential biomarker for evaluating the prognosis and therapeutic efficacy in NSCLC patients.

Knockdown of RRM1 with Adenoviral shRNA Vectors to Inhibit Tumor Cell Viability and Increase Chemotherapeutic Sensitivity to Gemcitabine in Bladder Cancer Cells

RRM1—an important DNA replication/repair enzyme—is the primary molecular gemcitabine (GEM) target. High RRM1-expression associates with gemcitabine-resistance in various cancers and RRM1 inhibition may provide novel cancer treatment approaches. Our study elucidates how RRM1 inhibition affects cancer cell proliferation and influences gemcitabine-resistant bladder cancer cells. Of nine bladder cancer cell lines investigated, two RRM1 highly expressed cells, 253J and RT112, were selected for further experimentation. An RRM1-targeting shRNA was cloned into adenoviral vector, Ad-shRRM1. Gene and protein expression were investigated using real-time PCR and western blotting. Cell proliferation rate and chemotherapeutic sensitivity to GEM were assessed by MTT assay. A human tumor xenograft model was prepared by implanting RRM1 highly expressed tumors, derived from RT112 cells, in nude mice. Infection with Ad-shRRM1 effectively downregulated RRM1 expression, significantly inhibiting cell growth in both RRM1 highly expressed tumor cells. In vivo, Ad-shRRM1 treatment had pronounced antitumor effects against RRM1 highly expressed tumor xenografts (p < 0.05). Moreover, combination of Ad-shRRM1 and GEM inhibited cell proliferation in both cell lines significantly more than either treatment individually. Cancer gene therapy using anti-RRM1 shRNA has pronounced antitumor effects against RRM1 highly expressed tumors, and RRM1 inhibition specifically increases bladder cancer cell GEM-sensitivity. Ad-shRRM1/GEM combination therapy may offer new treatment options for patients with GEM-resistant bladder tumors.

Plasmacytoid urothelial carcinoma (UC) are luminal tumors with similar immune microenvironment as compared to conventional UC.

477 Background:Plasmacytoid urothelial carcinoma (UC) is a rare pathological variant of UC with low chemotherapeutic sensitivity and dismal outcomes. The molecular and immune profiles of such tumors remain poorly investigated. Herein, we investigated the phenotypical features of a cohort of plasmacytoid UC (n = 32) by comparison to a control group of conventional high-grade UC with matched clinicopathological characteristics (n = 30). Methods: Histopathological analysis included the following antibodies: p63, GATA3, CK5/6, CK20 and HER2. In addition, the density of intra-tumor CD8+ lymphocytes, and PD-L1 expression in tumor (TC) and immune cells (IC) were evaluated. Clinical data were collected. Results: Plasmacytoid UC expressed GATA3 (97% vs 86% p = 0.18), CK20 (59% vs 36% p = 0.08) markers and showed a significantly higher rate of HER2 overexpression (2+ and 3+ score: 25% vs 0%, p < 0.01) compared to controls. A significantly lower expression of CK5/6 (22% vs 56%, p < 0.05) and p63 (41% vs 80%, p < 0.05) was observed in plasmacytoid UC compared to controls. The density of tumor-infiltrating CD8+ cells was similar between plasmacytoid and conventional UC (p = 0.5). PD-L1 expression on IC was similar compared to conventional UC (p = 0.3). Overall survival at 5 years was significantly lower among patients with plasmacytoid UC compared to patients with conventional UC (p = 0.02). Conclusions: Together, our study demonstrated that plasmacytoid UC belong to the luminal subtype and display a rather inflamed microenvironment similar to conventional UC. These data support the inclusion of plasmacytoid variant of UC in clinical trials evaluating immune checkpoint inhibitors monotherapy or combination immunotherapeutic strategies.

RIP3 mediates TCN-induced necroptosis through activating mitochondrial metabolism and ROS production in apoptosis-resistant cancer cells

Background: Resisting cell death is one of the hallmarks of cancer. Necroptosis is a form of non-caspase dependent necrotic cell death mediated by receptor-interacting protein kinase-1/3 (RIP1/3), which represents another mode of programmed cell death besides apoptosis. Growing evidence supports that RIP3 has emerged as a critical regulator of necroptosis and can be activated by several stimuli to trigger necroptotic cell death in a RIP1-independent manner. RIP3 also acts as an energy metabolism regulator associated with switching cell death from apoptosis to necroptosis. Natural products provide a unique source for the discovery of innovative leading compounds and drugs, which exhibits promising anticancer activities through inducing cell death and enhancing chemotherapeutic sensitivity. Trichothecin (TCN) is a sesquiterpenoid originating from an endophytic fungus of the herbal plant Maytenus hookeri Loes and shows potent anti-tumor bioactivity. However, the underlying mechanism is not fully understood.Methods: Cell permeability assay and transmission electron microscopy were applied to identify the death pattern induced by TCN in apoptotic-resistant cancer cells. We used Seahorse extracellular flux analyzer to examine the cellular oxygen consumption rate (OCR) and flow cytometry to detect mitochondrial reactive oxygen species (ROS) content. Xenograft animal experiment was performed to assess the effect of TCN synergized with cisplatin to enhance chemotherapeutic sensitivity of tumor cells. Results: Our current findings revealed that RIP3 mediated TCN-induced necroptosis through activating mitochondria energy metabolism and ROS production in apoptotic-resistant cancer cells. RIP3 might be involved in sensitizing tumor cells to chemotherapy induced by TCN. Conclusions: Activating RIP3 to induce necroptosis through reprogramming mitochondrial energy metabolism and ROS production contributes to the anti-tumor activity of TCN. Moreover, TCN could be exploited for therapeutic gain through up-regulating RIP3 to sensitize cancer chemotherapy.