Chemotherapeutic Drug Response Research Articles

Exploring the influence of microgravity on chemotherapeutic drug response in cancer: Unveiling new perspectives.

Microgravity, an altered gravity condition prevailing in space, has been reported to have a profound impact on human health. Researchers are very keen to comprehensively investigate the impact of microgravity and its intricate involvement in inducing physiological changes. Evidenced transformations were observed in the internal architecture including cytoskeletal organization and cell membrane morphology. These alterations can significantly influence cellular function, signalling pathways and overall cellular behaviour. Further, microgravity has been reported to alter in the expression profile of genes and metabolic pathways related to cellular processes, signalling cascades and structural proteins in cancer cells contributing to the overall changes in the cellular architecture. To investigate the effect of microgravity on cellular and molecular levels numerous ground-based simulation systems employing both invitro and invivo models are used. Recently, researchers have explored the possibility of leveraging microgravity to potentially modulate cancer cells against chemotherapy. These findings hold promise for both understanding fundamental processes and could potentially lead to the development of more effective, personalized and innovative approaches in therapeutic advancements against cancer.

Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6’s role in hematopoietic differentiation and leukemia

BackgroundLong non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns render them attractive biomarkers and therapeutic targets. Yet, the functional roles of most lncRNAs remain enigmatic. To address the need to identify new druggable lncRNAs, we developed a comprehensive approach integrating transcription factor binding data with other genetic features to generate a machine learning model, which we have called INFLAMeR (Identifying Novel Functional LncRNAs with Advanced Machine Learning Resources).MethodsINFLAMeR was trained on high-throughput CRISPR interference (CRISPRi) screens across seven cell lines, and the algorithm was based on 71 genetic features. To validate the predictions, we selected candidate lncRNAs in the human K562 leukemia cell line and determined the impact of their knockdown (KD) on cell proliferation and chemotherapeutic drug response. We further performed transcriptomic analysis for candidate genes. Based on these findings, we assessed the lncRNA small nucleolar RNA host gene 6 (SNHG6) for its role in myeloid differentiation. Finally, we established a mouse K562 leukemia xenograft model to determine whether SNHG6 KD attenuates tumor growth in vivo.ResultsThe INFLAMeR model successfully reconstituted CRISPRi screening data and predicted functional lncRNAs that were previously overlooked. Intensive cell-based and transcriptomic validation of nearly fifty genes in K562 revealed cell type-specific functionality for 85% of the predicted lncRNAs. In this respect, our cell-based and transcriptomic analyses predicted a role for SNHG6 in hematopoiesis and leukemia. Consistent with its predicted role in hematopoietic differentiation, SNHG6 transcription is regulated by hematopoiesis-associated transcription factors. SNHG6 KD reduced the proliferation of leukemia cells and sensitized them to differentiation. Treatment of K562 leukemic cells with hemin and PMA, respectively, demonstrated that SNHG6 inhibits red blood cell differentiation but strongly promotes megakaryocyte differentiation. Using a xenograft mouse model, we demonstrate that SNHG6 KD attenuated tumor growth in vivo.ConclusionsOur approach not only improved the identification and characterization of functional lncRNAs through genomic approaches in a cell type-specific manner, but also identified new lncRNAs with roles in hematopoiesis and leukemia. Such approaches can be readily applied to identify novel targets for precision medicine.

Saturation genome editing of 11 codons and exon 13 of BRCA2 coupled with chemotherapeutic drug response accurately determines pathogenicity of variants.

The unknown pathogenicity of a significant number of variants found in cancer-related genes is attributed to limited epidemiological data, resulting in their classification as variant of uncertain significance (VUS). To date, Breast Cancer gene-2 (BRCA2) has the highest number of VUSs, which has necessitated the development of several robust functional assays to determine their functional significance. Here we report the use of a humanized-mouse embryonic stem cell (mESC) line expressing a single copy of the human BRCA2 for a CRISPR-Cas9-based high-throughput functional assay. As a proof-of-principle, we have saturated 11 codons encoded by BRCA2 exons 3, 18, 19 and all possible single-nucleotide variants in exon 13 and multiplexed these variants for their functional categorization. Specifically, we used a pool of 180-mer single-stranded donor DNA to generate all possible combination of variants. Using a high throughput sequencing-based approach, we show a significant drop in the frequency of non-functional variants, whereas functional variants are enriched in the pool of the cells. We further demonstrate the response of these variants to the DNA-damaging agents, cisplatin and olaparib, allowing us to use cellular survival and drug response as parameters for variant classification. Using this approach, we have categorized 599 BRCA2 variants including 93-single nucleotide variants (SNVs) across the 11 codons, of which 28 are reported in ClinVar. We also functionally categorized 252 SNVs from exon 13 into 188 functional and 60 non-functional variants, demonstrating that saturation genome editing (SGE) coupled with drug sensitivity assays can enhance functional annotation of BRCA2 VUS.

A study on metabolic characteristics and metabolic markers of gastrointestinal tumors

ABSTRACT Tumor cells have significant heterogeneity in metabolism and are closely related to prognosis, gene mutation, and subtype. However, this association has not been demonstrated in reports of gastrointestinal tumors. In this study, we constructed four metabolic subtypes and identified four gene signatures using the expression data and clinical information of 252 metabolism-related genes from TCGA and NCBI databases for gastric adenocarcinoma (STAD) and colorectal cancer (COAD and READ). MC1 had the worst prognosis compared to other classifications. GSig1 was mainly related to drug metabolism and was the highest in MC1 with the worst prognosis, while the other subtypes were mainly related to glucose metabolism pathways. This difference also existed in other different malignant tumors. In addition, metabolic typing was associated with chemotherapeutic drug response and tumor heterogeneity, which indicated that monitoring metabolic typing could contribute to drug efficacy and gene-targeted therapy. In conclusion, we identified differences among subtypes in clinical characteristics such as prognosis and revealed the potential function of metabolic subtype in response to chemotherapeutic agents and oncogene mutations. This work highlighted the potential clinical meaning of metabolic subtype and characteristics in drug therapy and prognosis assessment of malignant tumors.

High-Precision Detection of Cellular Drug Response Based on SERS Spectrum and Multivariate Statistical Analysis

The rapid development of personalized medicine places high demands on the control of drug dose and cellular drug response to provide patients with better curative effects and low side effects. To solve the problem of low detection accuracies of the cell-counting kit-8 (CCK8) method, a detection method based on surface-enhanced Raman spectroscopy (SERS) of cell-secreted proteins was adopted to evaluate the concentration of the anticancer drug cisplatin and the cellular drug response of nasopharyngeal carcinoma. CNE1 and NP69 cell lines were used to evaluate cisplatin response. The results showed that the combination of the SERS spectrum with principal component analysis-linear discriminant analysis could detect the difference in the response of cisplatin with a concentration difference of 1 μg/mL, which considerably exceeded that of CCK8. In addition, the SERS spectral peak intensity of the cell-secreted proteins strongly correlated with the cisplatin concentration. Furthermore, the mass spectrum of the secreted proteins of the nasopharyngeal carcinoma cells was analyzed to verify the results obtained using the SERS spectrum. The results demonstrated that SERS of secreted proteins has great potential for high-precision detection of chemotherapeutic drug response.

M6A-Related lncRNA Signature Is Involved in Immunosuppression and Predicts the Patient Prognosis of the Age-Associated Ovarian Cancer.

Background Epithelial ovarian cancers are age-associated diseases, usually diagnosed at an advanced stage. lncRNA has been discovered to interplay with N6-methyladenosine (m6A), working in tandem to promote cancer progression and worsening patient outcomes. This study is aimed at investigating the roles and mechanism of m6A-related lncRNA signature on ovarian cancers. Methods We retrieved TCGA and CGGA sequencing data to identify m6A-related lncRNA signature and constructed an m6A score (MS) using the LASSO algorithm. A clinical nomogram was then established to predict the overall survival of patients. Subsequently, GSEA analyses were conducted to obtain pathways involved. Expression of HLA genes, 28 tumor-infiltrating lymphocyte infiltration, and anticancer cycle were analyzed the immunological differences between high-MS and low-MS groups. Finally, immune checkpoint gene expressions and IC50 of chemotherapeutic drugs were calculated, and CMap was run to identify the potential compounds and their corresponding mechanisms. Results We identified 16 m6A-related lncRNAs and constructed an MS model. The high-MS group showed a poor prognosis. A clinical nomogram consists of MS, and age was constructed and predicted the 1-, 3-, and 5-year survival with high accuracy. GSEA analyses presented downregulated antigen processing and presentation pathways. Immunocyte infiltrating analyses demonstrated that high-MS was associated with high infiltration of Treg cells, macrophages, and low Th1/Th2 rate. Also, high expression of immune checkpoint genes NRP1, TNFSF9, and VSIR was observed in the high-MS group. Finally, the high-MS group also predicted low IC50 of vinorelbine and vorinostat. Conclusion This study constructed a robust prediction model for prognostic management and revealed the cross-talk between m6A and immunosuppression. Besides, the m6A lncRNA signature can predict the chemotherapeutic drug response. These will shed light on the development of novel therapeutic strategies and render survival benefits for ovarian patients.

The Multi-Omics Landscape and Clinical Relevance of the Immunological Signature of Phagocytosis Regulators: Implications for Risk Classification and Frontline Therapies in Skin Cutaneous Melanoma.

Simple SummaryIn this study, we focused on exploring phagocytosis regulators’ expression and mutational characteristics in skin cutaneous melanoma samples and delineating two molecular subtypes based on expression characteristics. We determined the relationship between phagocytosis regulators and survival by survival analysis of molecular subtypes. We then constructed a survival model (PRRS) to further quantify the criteria. Moreover, we combined pathway analysis, immune infiltration analysis, and mutation analysis to deeply explore the effects of phagocytosis regulators on skin cutaneous melanoma samples.Tumor-associated macrophages (TAMs) have gained considerable attention as therapeutic targets. Monoclonal antibody treatments directed against tumor antigens contribute significantly to cancer cell clearance by activating macrophages to phagocytose tumor cells. Due to its complicated genetic and molecular pathways, skin cutaneous melanoma (SKCM) has not yet attained the expected clinical efficacy and prognosis when compared to other skin cancers. Therefore, we chose TAMs as an entrance point. This study aimed to thoroughly assess the dysregulation and regulatory role of phagocytosis regulators in SKCM, as well as to understand their regulatory patterns in SKCM. This study subtyped prognosis-related phagocytosis regulators to investigate prognostic differences between subtypes. Then, we screened prognostic factors and constructed phagocytosis-related scoring models for survival prediction using differentially expressed genes (DEGs) between subtypes. Additionally, we investigated alternative treatment options using chemotherapeutic drug response data and clinical cohort treatment data. We first characterized and generalized phagocytosis regulators in SKCM and extensively examined the tumor immune cell infiltration. We created two phagocytosis regulator-related system (PRRS) phenotypes and derived PRRS scores using a principal component analysis (PCA) technique. We discovered that subtypes with low PRRS scores had a poor prognosis and decreased immune checkpoint-associated gene expression levels. We observed significant therapeutic and clinical improvements in patients with higher PRRS scores. Our findings imply that the PRRS scoring system can be employed as an independent and robust prognostic biomarker, serving as a critical reference point for developing novel immunotherapeutic methods.

Abstract 3080: A quality-controlled patient-derived tumor organoid biobank facilitates applications such as an integrated database of chemotherapeutic drug response using deep learning-based imaging methods

Abstract Patient-derived tumor organoids (PDTOs) have recently been used as an innovative preclinical model to predict patient-specific drug responses. However, it is critical to establish high quality, reproducible, and well-annotated PDTOs that closely recapitulate the original tumors from which they were derived. Here, we established a biobank of over 20 colorectal cancer (CRC) PDTOs representing a racially and ethnically diverse patient population that has been subjected to rigorous quality control (QC) measures. We demonstrate the utility of a well-characterized biobank across several applications including the development of an integrated chemotherapeutic drug response database and image-based phenotypic analyses using deep-learning neural networks (NNs). To ensure consistency across our biobank, PDTOs were subjected to a meticulous processing pipeline which includes the extensive collection of pertinent culturing metadata (i.e., multi-timepoint brightfield images pre- and post-passaging for consistent size and health of the PDTOs, short tandem repeat sequencing to establish a unique patient barcode, and routine mycoplasma testing results to minimize contamination) and DNA/RNA sequencing to verify the PDTOs reflect the genetic profile of the original tumor. A dashboard is used to manage culturing and characterization tasks across the Cell Line Team and samples are registered in a Lab Information Management System (LIMS) for tracking of data associated with the samples, including detailed patient information. Our high-quality biobank supports a diverse project portfolio including the creation of a database of PDTO drug responses to clinically-approved chemotherapy treatments 5-Fluorouracil and Irinotecan. This database compares PDTO-specific dose-response curves between ATP-based viability assays and image-based NN analysis and we found the IC50 values from the two analytical methods to be comparable. The NNs were designed to segment and classify organoids as live or dead from brightfield images. The label-free, non-destructive nature of this method enables dynamic imaging and analysis over multiple timepoints. Notably, our biobank and NN analysis work in concert where the biobank provides valuable, consistent datasets that are used to train and validate NNs and the NN is subsequently used to understand phenotypic drug responses of PDTOs. From these results we can show inter-patient heterogeneity in drug responses. In conclusion, we generated a reliable biobank to support numerous applications including the creation of a PDTO drug response database with deep learning validation. Such a biobank is only feasible through meticulous QC and can serve as a great resource to understand treatment outcomes and identify better therapeutic options for patients in the future. Citation Format: Scott Valena, Pratiksha Kshetri, Brandon Choi, Ah Young Yoon, Shohei Imamura, Seungil Kim, Michael E. Doche, Shannon M. Mumenthaler. A quality-controlled patient-derived tumor organoid biobank facilitates applications such as an integrated database of chemotherapeutic drug response using deep learning-based imaging methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3080.

Patient-Derived Organoid Model in the Prediction of Chemotherapeutic Drug Response in Colorectal Cancer.

As an emerging technology in precision medicine, the patient-derived organoid (PDO) technology has been indicated to provide novel modalities to judge the sensitivity of individual tumors to cancer drugs. In this work, an in vitro model of colorectal cancer (CRC) was established using the PDO culture, and it is demonstrated that the PDO samples preserved, to a great extent, the histologic features and marker expression of the original tumor tissues. Subsequently, cancer drugs 5-FU, oxaliplatin, and irinotecan were selected and screened on five CRC PDO samples, while the patient-derived organoid xenograft (PDOX) model was applied for comparison. The receiver operating characteristic (ROC) curve was drawn according to the IC50 data from the PDO model and the relative tumor proliferation rate (T/C%) from PDOX. Interestingly, the area under the ROC curve was 0.84 (95% CI, 0.64-1.04, P value = 0.028), which suggested that the IC50 of cancer drugs from the PDO model was strongly correlated with PDOX responses. In addition, the optimal sensitivity cutoff value for drug screening in CRC PDOs was identified at 10.35 μM, which could act as a reference value for efficacy evaluation of 5-FU, oxaliplatin, and irinotecan in the colorectal cancer drug screening. Since there are no unified criteria to judge the sensitivity of drugs in vitro, our work provides a method for establishing in vitro evaluation criteria via PDO and PDOX model using the patient tissues received from local hospitals, exhibiting potential in clinical cancer therapy and precision medicine.

METTL3 promotes homologous recombination repair and modulates chemotherapeutic response in breast cancer by regulating the EGF/RAD51 axis.

Methyltransferase-like 3 (METTL3) and N6-methyladenosine (m6A) are involved in many types of biological and pathological processes, including DNA repair. However, the function and mechanism of METTL3 in DNA repair and chemotherapeutic response remain largely unknown. In present study, we identified that METTL3 participates in the regulation of homologous recombination repair (HR), which further influences chemotherapeutic response in both MCF-7 and MDA-MB-231 breast cancer (BC) cells. Knockdown of METTL3 sensitized these BC cells to Adriamycin (ADR; also named as doxorubicin) treatment and increased accumulation of DNA damage. Mechanically, we demonstrated that inhibition of METTL3 impaired HR efficiency and increased ADR-induced DNA damage by regulating m6A modification of EGF/RAD51 axis. METTL3 promoted EGF expression through m6A modification, which further upregulated RAD51 expression, resulting in enhanced HR activity. We further demonstrated that the m6A 'reader,' YTHDC1, bound to the m6A modified EGF transcript and promoted EGF synthesis, which enhanced HR and cell survival during ADR treatment in BC. Our findings reveal a pivotal mechanism of METTL3-mediated HR and chemotherapeutic drug response, which may contribute to cancer therapy.

A Pleiotropic Role of Long Non-Coding RNAs in the Modulation of Wnt/β-Catenin and PI3K/Akt/mTOR Signaling Pathways in Esophageal Squamous Cell Carcinoma: Implication in Chemotherapeutic Drug Response.

Despite the availability of modern techniques for the treatment of esophageal squamous cell carcinoma (ESCC), tumor recurrence and metastasis are significant challenges in clinical management. Thus, ESCC possesses a poor prognosis and low five-year overall survival rate. Notably, the origin and recurrence of the cancer phenotype are under the control of complex cancer-related signaling pathways. In this review, we provide comprehensive knowledge about long non-coding RNAs (lncRNAs) related to Wnt/β-catenin and phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway in ESCC and its implications in hindering the efficacy of chemotherapeutic drugs. We observed that a pool of lncRNAs, such as HERES, TUG1, and UCA1, associated with ESCC, directly or indirectly targets various molecules of the Wnt/β-catenin pathway and facilitates the manifestation of multiple cancer phenotypes, including proliferation, metastasis, relapse, and resistance to anticancer treatment. Additionally, several lncRNAs, such as HCP5 and PTCSC1, modulate PI3K/Akt/mTOR pathways during the ESCC pathogenesis. Furthermore, a few lncRNAs, such as AFAP1-AS1 and LINC01014, block the efficiency of chemotherapeutic drugs, including cisplatin, 5-fluorouracil, paclitaxel, and gefitinib, used for ESCC treatment. Therefore, this review may help in designing a better therapeutic strategy for ESCC patients.

Abstract 3164: Modeling the metastatic niche interactions between patient tumor and mesenchymal cells to identify drivers of chemotherapy drug resistance

Abstract Cancer research relies on a plethora of disease-relevant tumor models, but patient specific models are still being developed. In this study, we show the utility of patient-specific pancreatic, ovarian and breast cancer models in the context of the metastatic niche, composed of co-cultured mesenchymal stem cells (MSC) in three-dimensional tumor spheroids. Additionally, different ratios of MSC's were seeded with the cancer spheroids to interrogate the effect of MSC's on chemotherapeutic drug response in defined media conditions. The patient-specific and treatment-naive cancer models represent a diverse range of disease type, progression grade, and genetic profiles. These models were co-cultured with MSC's sourced from both bone marrow and adipose tissue. These co-culture models were tested with a panel of common, broad-range chemotherapeutic agents as well as several disease-specific drugs. The resulting drug responses show that the presence of MSC's within the context of the metastatic niche causes attenuation towards a higher chemotherapeutic drug resistance. The tumor models exhibit a varied chemotherapeutic response when MSC's are seeded in 50:1, 5:1, or 1:1 ratio with cancer cells, suggesting that even a small presence of MSC's may have a significant effect on the drug resistance of metastatic tumor spheroids. While this MSC-induced drug response attenuation is observed across the broad spectrum of patient profiles and disease types, the strength of the effect is not homogenous. The observed variability in the strength of the effect was impacted by the disease type of the cancer cells, the source of the MSC's, and the specific drug used in the metastatic tumor model. We propose that using these reproducible and easily scaled models of metastatic tumors to find effective chemotherapeutic drugs could increase our understanding of the tumor microenvironment, the onset of metastasis, and the process of cancer grafting into other tissues. Discovering effective and targeted therapies utilizing a more advanced model of the metastatic tumor niche could increase the success rate of an eventual clinical trial. Citation Format: Liam Deems, Amit Shahar, Amy Pepicelli, Cheryl Murphy, Daniel Solomon, David Deems, Dmitry Shvartsman. Modeling the metastatic niche interactions between patient tumor and mesenchymal cells to identify drivers of chemotherapy drug resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3164.

Reciprocal regulation between GCN2 (eIF2AK4) and PERK (eIF2AK3) through the JNK-FOXO3 axis to modulate cancer drug resistance and clonal survival

Pharmaceutical inhibitors of the endoplasmic reticulum (ER)-stress modulator PERK (eIF2AK3) have demonstrated anticancer activities in combination therapies, but their effectiveness as a single agent is limited, suggesting the existence of possible compensatory cellular responses. To explore the potential mechanisms involved, we performed time-course drug treatment experiments on the parental MCF-7 and drug resistant MCF-7EpiR and MCF-7TaxR breast cancer cells and identified GCN2 (eIF2AK4) as a molecule that can potentially cooperate with PERK to regulate FOXO3 via JNK and AKT to modulate drug response. Consistently, GCN2 knockdown severely impaired the clonal survival of parental and resistant MCF-7 cells and sensitised them to epirubicin and paclitaxel treatment. Western blot, RT-qPCR and ChIP analyses also confirmed that GCN2 inactivation causes an induction of JNK and thereby FOXO3 activity, culminating in an increase in PERK activity and expression at the transcription level. Conversely, PERK-inactivation using GSK2606414-induces an induction in GCN2 expression and activity also associated with JNK. In agreement, we also showed that the perk−/− MEFs, expressing elevated levels of P-JNK, JNK, GCN2 and reduced levels of P-AKT and P-FOXO3, have lower clonogenicity and are more sensitive to epirubicin compared to wild-type MEFs. Similarly, gcn2−/− MEFs expressing augmented levels of P-JNK, JNK, P-PERK, PERK and lower levels of P-AKT and P-FOXO3 also had lower clonogenicity and were more sensitive to epirubicin and PERK-inhibition. In addition, JNK1/2 deletion in MEFs resulted in reduced levels of GCN2, FOXO3, PERK, P-PERK expression as well as FOXO3 activity and enhanced clonal survival and resistance to PERK-inhibition. Together these results demonstrate that GCN2 cooperates with PERK through the JNK-FOXO3 axis in a reciprocal negative feedback loop to mediate cancer chemotherapeutic drug response and clonal survival, advocating the potential of targeting GCN2 as a therapeutic strategy for treating cancer and for overcoming drug resistance.

Gene regulatory network analysis with drug sensitivity reveals synergistic effects of combinatory chemotherapy in gastric cancer

The combination of docetaxel, cisplatin, and fluorouracil (DCF) is highly synergistic in advanced gastric cancer. We aimed to explain these synergistic effects at the molecular level. Thus, we constructed a weighted correlation network using the differentially expressed genes between Stage I and IV gastric cancer based on The Cancer Genome Atlas (TCGA), and three modules were derived. Next, we investigated the correlation between the eigengene of the expression of the gene network modules and the chemotherapeutic drug response to DCF from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The three modules were associated with functions related to cell migration, angiogenesis, and the immune response. The eigengenes of the three modules had a high correlation with DCF (−0.41, −0.40, and −0.15). The eigengenes of the three modules tended to increase as the stage increased. Advanced gastric cancer was affected by the interaction the among modules with three functions, namely cell migration, angiogenesis, and the immune response, all of which are related to metastasis. The weighted correlation network analysis model proved the complementary effects of DCF at the molecular level and thus, could be used as a unique methodology to determine the optimal combination of chemotherapy drugs for patients with gastric cancer.

The role of miR-34 in cancer drug resistance.

Resistance to conventional chemotherapy remains a major cause of cancer relapse and cancer-related deaths. Therefore, there is an urgent need to overcome resistance barriers. To improve cancer treatment approaches, it is critical to elucidate the basic mechanisms underlying drug resistance. Increasingly, the mechanisms involving micro-RNAs (miRNAs) are studied because miRNAs are also considered practical therapeutic options due to high degrees of specificity, efficacy, and accuracy, as well as their ability to target multiple genes at the same time. Years of research have firmly established miR-34 as a key tumor suppressor miRNA whose target genes are involved in drug resistance mechanisms. Indeed, numerous articles show that low levels of circulating miR-34 or tumor-specific miR-34 expression are associated with poor response to chemotherapy. In addition, elevation of inherently low miR-34 levels in resistant cancer cells effectively restores sensitivity to chemotherapeutic agents. Here, we review this literature, also highlighting some contradictory observations. In addition, we discuss the potential utility of miR-34 expression as a predictive biomarker for chemotherapeutic drug response. Although caution needs to be exercised, miR-34 is emerging as a biomarker that could improve cancer precision medicine.

Nipped-B-like Protein Sensitizes Esophageal Squamous Cell Carcinoma Cells to Cisplatin via Upregulation of PUMA.

Nipped-B-like protein plays a pivotal role as a cohesin loading factor in the segregation of chromosomes when cells divide. Accumulating evidence indicates that alterations of this protein are involved in human carcinogenesis, especially in the regulation of chemotherapeutic drug response. However, the role of Nipped-B-like protein in esophageal squamous cell carcinoma remains unknown. In this study, we investigated the relevance of Nipped-B-like protein in the regulation of cisplatin sensitivity in esophageal squamous cell carcinoma. Ectopic expression of Nipped-B-like protein inhibited the growth of COLO-680N cells with low endogenous expression levels of Nipped-B-like protein, and increased sensitivity to cisplatin, a commonly used chemotherapy drug for patients with esophageal squamous cell carcinoma. In contrast, loss of Nipped-B-like protein stimulated the growth of EC9706 and Eca-109 cells with high levels of the protein, and resulted in resistance to cisplatin. P53-upregulated modulator of apoptosis, which is essential in the modulation of cisplatin sensitivity in a variety of cancers, acts as a downstream effector of Nipped-B-like protein. Restoration of this pro-apoptotic protein in Nipped-B-like protein-overexpressing esophageal squamous cell carcinoma cells effectively increased cisplatin sensitivity. Conversely, the silencing of P53-upregulated modulator of apoptosis in Nipped-B-like protein-depleted esophageal squamous cell carcinoma rendered cells resistant to cisplatin. Moreover, Nipped-B-like protein could bind directly to the promoter region of P53-upregulated modulator of apoptosis. In summary, our study addresses the involvement of Nipped-B-like protein in the development of esophageal squamous cell carcinoma, and the modulation of cisplatin sensitivity via regulation of P53-upregulated modulator of apoptosis.

CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids.

Background Organoid cultures of human pancreatic ductal adenocarcinoma (PDAC) have become a promising tool for tumor subtyping and individualized chemosensitivity testing. PDACs have recently been grouped into different molecular subtypes with clinical impact based on cytokeratin-81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A). However, a suitable antibody for HNF1A is currently unavailable. The present study is aimed at establishing subtyping in PDAC organoids using an alternative marker. Methods A PDAC organoid biobank was generated from human primary tumor samples containing 22 lines. Immunofluorescence staining was established and done for 10 organoid lines for cystic fibrosis transmembrane conductance regulator (CFTR) and KRT81. Quantitative real-time PCR (qPCR) was performed for CFTR and HNF1A. A chemotherapeutic drug response analysis was done using gemcitabine, 5-FU, oxaliplatin, and irinotecan. Results A biobank of patient-derived PDAC organoids was established. The efficiency was 71% (22/31) with 68% for surgical resections and 83% for fine needle aspirations. Organoids could be categorized into the established quasimesenchymal, exocrine-like, and classical subtypes based on KRT81 and CFTR immunoreactivity. CFTR protein expression was confirmed on the transcript level. CFTR and HNF1A transcript expression levels positively correlated (n = 10; r = 0.927; p = 0.001). PDAC subtypes of the primary tumors and the corresponding organoid lines were identical for most of the cases analyzed (6/7). Treatment with chemotherapeutic drugs revealed tendencies but no significant differences regarding drug responses. Conclusions Human PDAC organoids can be classified into known subtypes based on KRT81 and CFTR immunoreactivity. CFTR and HNF1A mRNA levels correlated well. Furthermore, subtype-specific immunoreactivity matched well between PDAC organoids and the respective primary tumor tissue. Subtyping of human PDACs using CFTR might constitute an alternative to HNF1A and should be further investigated.

Human Microbiota and Personalized Cancer Treatments: Role of Commensal Microbes in Treatment Outcomes for Cancer Patients.

The human gut microbiota consists of about 3.8 × 1013 microorganisms that play an essential role in health, metabolism, and immunomodulation. These gut microbes alter therapeutic response and toxicity to cancer therapies including cytotoxic chemotherapy, radiation therapy, kinase inhibitors, and immunotherapy agents. The gut microbiota generates short-chain fatty acids that are significant regulators of histone post-translational modifications that fundamentally regulate gene expression, linking the microbiota to cellular metabolism and transcriptional regulation. The short-chain fatty acids not only act locally but can be taken up in the blood stream to inhibit the activity of histone deacetylases, regulate gene expression in distant organs as well as the effector function of CD8+ T cells. Cancer and the treatments for it negatively impact the microbiome often resulting in dysbiosis. This can diminish a patient's response to treatment as well as increase systemic toxicities from these therapies. In addition to the gut microbiota, microbes have been detected in tumors that can modulate chemotherapeutic drug response and can result in immune suppression. The gut microbiota and tumor-associated bacteria may be a significant contributor to the interindividual differences and heterogeneous responses to cancer therapies and drug tolerability and strategies that support and/or manipulate the microbiota to improve therapeutic outcomeis an emerging area for personalized cancer treatment.

NFIB promotes cell survival by directly suppressing p21 transcription in TP53-mutated triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited treatment options and poor prognosis. There is an urgent need to identify and understand the key factors and signalling pathways driving TNBC tumour progression, relapse, and treatment resistance. In this study, we report that gene copy numbers and expression levels of nuclear factor IB (NFIB), a recently identified oncogene in small cell lung cancer, are preferentially increased in TNBC compared to other breast cancer subtypes. Furthermore, increased levels of NFIB are significantly associated with high tumour grade, poor prognosis, and reduced chemotherapy response. Concurrent TP53 mutations and NFIB overexpression (z-scores > 0) were observed in 77.9% of TNBCs, in contrast to 28.5% in non-TNBCs. Depletion of NFIB in TP53-mutated TNBC cell lines promotes cell death, cell cycle arrest, and enhances sensitivity to docetaxel, a first-line chemotherapeutic drug in breast cancer treatment. Importantly, these alterations in growth properties were accompanied by induction of CDKN1A, the gene encoding p21, a downstream effector of p53. We show that NFIB directly interacts with the CDKN1A promoter in TNBC cells. Furthermore, knockdown of combined p21 and NFIB reverses the docetaxel-induced cell growth inhibition observed upon NFIB knockdown, indicating that NFIB's effect on chemotherapeutic drug response is mediated through p21. Our results indicate that NFIB is an important TNBC factor that drives tumour cell growth and drug resistance, leading to poor clinical outcomes. Thus, targeting NFIB in TP53-mutated TNBC may reverse oncogenic properties associated with mutant p53 by restoring p21 activity. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

New tools for old drugs: Functional genetic screens to optimize current chemotherapy.

Despite substantial advances in the treatment of various cancers, many patients still receive anti-cancer therapies that hardly eradicate tumor cells but inflict considerable side effects. To provide the best treatment regimen for an individual patient, a major goal in molecular oncology is to identify predictive markers for a personalized therapeutic strategy. Regarding novel targeted anti-cancer therapies, there are usually good markers available. Unfortunately, however, targeted therapies alone often result in rather short remissions and little cytotoxic effect on the cancer cells. Therefore, classical chemotherapy with frequent long remissions, cures, and a clear effect on cancer cell eradication remains a corner stone in current anti-cancer therapy. Reliable biomarkers which predict the response of tumors to classical chemotherapy are rare, in contrast to the situation for targeted therapy. For the bulk of cytotoxic therapeutic agents, including DNA-damaging drugs, drugs targeting microtubules or antimetabolites, there are still no reliable biomarkers used in the clinic to predict tumor response. To make progress in this direction, meticulous studies of classical chemotherapeutic drug action and resistance mechanisms are required. For this purpose, novel functional screening technologies have emerged as successful technologies to study chemotherapeutic drug response in a variety of models. They allow a systematic analysis of genetic contributions to a drug-responsive or −sensitive phenotype and facilitate a better understanding of the mode of action of these drugs. These functional genomic approaches are not only useful for the development of novel targeted anti-cancer drugs but may also guide the use of classical chemotherapeutic drugs by deciphering novel mechanisms influencing a tumor’s drug response. Moreover, due to the advances of 3D organoid cultures from patient tumors and in vivo screens in mice, these genetic screens can be applied using conditions that are more representative of the clinical setting. Patient-derived 3D organoid lines furthermore allow the characterization of the “essentialome”, the specific set of genes required for survival of these cells, of an individual tumor, which could be monitored over the course of treatment and help understanding how drug resistance evolves in clinical tumors. Thus, we expect that these functional screens will enable the discovery of novel cancer-specific vulnerabilities, and through clinical validation, move the field of predictive biomarkers forward. This review focuses on novel advanced techniques to decipher the interplay between genetic alterations and drug response.