Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

Identification of a novel immune-related gene signature by single-cell and bulk sequencing for the prediction of the immune landscape and prognosis of breast cancer

BACKGROUND

As a common cause of cancer-related deaths in women, BRCA (breast cancer) shows complexity and requires precise biomarkers and treatment methods. This study delves into the molecular makeup of BRCA, focusing on immune profiles, molecular subtypes, gene expression and single-cell analysis.

METHODS

XCell was used to assess immune infiltration based on TCGA (the Cancer Genome Atlas) data and the clustering analysis was made. Differentially expressed genes were examined in distinct clusters, and the WGCNA (weighted correlation network analysis) was made to establish co-expression networks. The prognostic models were developed by Cox and LASSO-Cox regression. The clustering analysis, GSEA (Gene set enrichment analysis), GSVA (gene set variation analysis) and communication analysis of the single-cell dataset GSE161529 were performed to investigate the functional relevance. Real-time polymerase chain reaction (RT-PCR) was employed for evaluating gene expression.

RESULTS

The results revealed significant differences in immune cell infiltration between two clusters (C1 and C2). C2 had poorer survival outcomes, which was associated with higher expression of immune checkpoints PD1 and PD-L1. The gene modules identified via WGCNA were correlated with the immune-based subtypes. Then, a prognostic model comprising seven genes (ACSL1, ABCB5, XG, ADH4, OPN4, NPR3, NLGN1) was used to divide patients into high- and low-risk subgroups. The high-risk group had worse prognosis and higher scores of TIDE (Tumor Immune Dysfunction and Exclusion). The single-cell analysis depicted the immune landscape. Macrophages and endothelial cells exhibited higher AUCell scores. In cellular communication analysis, notably significant ligand-receptor interactions of HLA-DRA-> CD4 and TNFSF13B-> HLA-DPB1 were observed. The proportion of endothelial cells was correlated with risk scores. Finally, RT-PCR results illustrated the expression of seven genes in BRCA specimens.

CONCLUSION

The integrative analysis provides new insights into molecular complexities of BRCA. Immune profiles and gene signatures hold potential for improving stratification of BRCA patients and guiding the development of personalized immunotherapy strategies.

Drug Response of Patient-Derived Lung Cancer Cells Predicts Clinical Outcomes of Targeted Therapy

Intratumor heterogeneity leads to different responses to targeted therapies, even within patients whose tumors harbor identical driver oncogenes. This study examined clinical outcomes according to a patient-derived cell (PDC)-based drug sensitivity test in lung cancer patients treated with targeted therapies. From 487 lung cancers, 397 PDCs were established with a success rate of 82%. In 139 PDCs from advanced non-small-cell lung cancer (NSCLC) patients receiving targeted therapies, the standardized area under the curve (AUC) values for the drugs was significantly correlated with their tumor response (p = 0.002). Among 59 chemo-naive EGFR/ALK-positive NSCLC patients, the PDC non-responders showed a significantly inferior response rate (RR) and progression-free survival (PFS) for the targeted drugs than the PDC responders (RR, 25% vs. 78%, p = 0.011; median PFS, 3.4 months [95% confidence interval (CI), 2.8-4.1] vs. 11.8 months [95% CI, 6.5-17.0], p < 0.001). Of 25 EGFR-positive NSCLC patients re-challenged with EGFR inhibitors, the PDC responder showed a higher RR than the PDC non-responder (42% vs. 15%). Four patients with wild-type EGFR or uncommon EGFR-mutant NSCLC were treated with EGFR inhibitors based on their favorable PDC response to EGFR inhibitors, and two patients showed dramatic responses. Therefore, the PDC-based drug sensitivity test results were significantly associated with clinical outcomes in patients with EGFR- or ALK-positive NSCLC. It may be helpful for predicting individual heterogenous clinical outcomes beyond genomic alterations.

The anti-tumor effects of AZD4547 on ovarian cancer cells: differential responses based on c-Met and FGF19/FGFR4 expression

BACKGROUND

The FGF/FGFR signaling pathway plays a critical role in human cancers. We analyzed the anti-tumor effect of AZD4547, an inhibitor targeting the FGF/FGFR pathway, in epithelial ovarian cancer (EOC) and strategies on overcoming AZD4547 resistance.

METHODS

The effect of AZD4547 on cell viability/migration was evaluated and in vivo experiments in intraperitoneal xenografts using EOC cells and a patient-derived xenograft (PDX) model were performed. The effect of the combination of AZD4547 with SU11274, a c-Met-specific inhibitor, FGF19-specific siRNA, or an FGFR4 inhibitor was evaluated by MTT assay.

RESULTS

AZD4547 significantly decreased cell survival and migration in drug-sensitive EOC cells but not drug-resistant cells. AZD4547 significantly decreased tumor weight in xenograft models of drug-sensitive A2780 and SKOV3ip1 cells and in a PDX with drug sensitivity but not in models with drug-resistant A2780-CP20 and SKOV3-TR cells. Furthermore, c-Met expression was high in SKOV3-TR and HeyA8-MDR cells, and co-administration of SU11274 and AZD4547 synergistically induced cell death. In addition, expressions of FGF19 and FGFR4 were high in A2780-CP20 cells. Combining AZD4547 with FGF19 siRNA or with a selective FGFR4 inhibitor led to significantly reduced cell proliferation in A2780-CP20 cells.

CONCLUSIONS

This study showed that AZD4547 has significant anti-cancer effects in drug-sensitive cells and PDX models but not in drug-resistant EOC cells. In drug-resistant cells, the expression level of c-Met or FGF19/FGFR4 may be a predictive biomarker for AZD4547 treatment response, and a combination strategy of drugs targeting c-Met or FGF19/FGFR4 together with AZD4547 may be an effective therapeutic strategy for EOC.

Clinicopathological and Prognostic Values of Telomerase Reverse Transcriptase (TERT) Promoter Mutations in Ovarian Clear Cell Carcinoma for Predicting Tumor Recurrence, Platinum Resistance and Survival

BACKGROUND/AIM

A small subset of patients with ovarian clear cell carcinoma (OCCC) harbors telomerase reverse transcriptase promoter (TERTp) mutations. We aimed to analyze the clinicopathological and molecular characteristics of TERTp-mutant OCCC and investigate whether TERTp mutations are associated with the clinicopathological characteristics and outcomes of patients with OCCC.

PATIENTS AND METHODS

We included 11 OCCC cases in our study. Targeted sequencing was performed with a thorough review of pathology slides and electronic medical records.

RESULTS

Eleven OCCCs harbored two hotspot TERTp mutations: c.1-146C>T (6/11) and c.1-124C>T (5/11). All patients (11/11) who underwent postoperative adjuvant chemotherapy experienced tumor recurrence, and eight of them were classified as platinum-resistant. TERTp-mutant OCCC showed significantly higher frequencies of postoperative recurrence and relapse within six months of chemotherapy. TERTp mutations significantly predicted disease-free survival (DFS) in patients with OCCC.

CONCLUSION

We demonstrate that TERTp mutations have significant prognostic value for predicting tumor recurrence, platinum resistance, and worse DFS in patients with OCCC.

High-throughput organo-on-pillar (high-TOP) array system for three-dimensional ex vivo drug testing

The development of organoid culture technologies has triggered industrial interest in ex vivo drug test-guided clinical response prediction for precision cancer therapy. The three-dimensional culture encapsulated with basement membrane (BM) components is extremely important in establishing ex vivo organoids and drug sensitivity tests because the BM components confer essential structures resembling tumor histopathology. Although numerous studies have demonstrated three-dimensional culture-based drug screening methods, establishing a large-scale drug-screening platform with matrix-encapsulated tumor cells is challenging because the arrangement of microspots of a matrix-cell droplet onto each well of a microwell plate is inconsistent and difficult to standardize. In addition, relatively low scales and lack of reproducibility discourage the application of three-dimensional organoid-based drug screening data for precision treatment or drug discovery. To overcome these limitations, we manufactured an automated organospotter-integrated high-throughput organo-on-pillar (high-TOP) drug-screening platform. Our system is compatible with various extracellular matrices, including BM extract, Matrigel, collagen, and hydrogel. In addition, it can be readily utilized for high-content analyses by simply exchanging the bottom plates without disrupting the domes. Our system demonstrated considerable robustness, consistency, reproducibility, and biological relevancy in three-dimensional drug sensitivity analyses using Matrigel-encapsulated ovarian cancer cell lines. We also demonstrated proof-of-concept cases representing the clinical feasibility of high-TOP-assisted ex vivo drug tests linked to clinical chemo-response in ovarian cancer patients. In conclusion, our platform provides an automated and standardized method for ex vivo drug-sensitivity-guided clinical response prediction, suggesting effective chemotherapy regimens for patients with cancer.

Somatic genomic landscape of East Asian epithelial ovarian carcinoma and its clinical implications from prospective clinical sequencing; A Korean Gynecologic Oncology Group study (KGOG 3047)

Through the wide adaptation of next-generation sequencing (NGS) technology within clinical practice, molecular profiling of the tumor has been the principal component of personalized treatment. In this study, we have generated a large collection of cancer genomes on East Asian epithelial ovarian carcinoma (EOC) patients and demonstrate the feasibility and utility of NGS platforms to explore the dynamic interrelations of major cancer driver alterations and their impacts on clinical prognosis and management. A total of 652 EOC patients have undergone clinical NGS panels to determine the prevalence of germline and somatic mutations. Notably, TP53 was the most frequently altered event (73%), followed by both BRCA1 and BRCA2 (22% each) and MYC (19%) through pan-EOC analysis. When analyzed based on individual histopathological levels, TP53 mutation was highly dominant in high-grade serous and mucinous histology, whereas mutations in PIK3CA and ARID1A were mostly observed in clear cell carcinoma, and KRAS, BRAF, and CDKN2A mutations were enriched in endometrioid, low-grade serous, and mucinous tumors, respectively. The network-based probabilistic model showed significant co-occurrences of TP53 with BRCA1 and ALK with BRCA2, NOTCH1, and ROS1, whereas mutual exclusivity of TP53 with KRAS and PIK3CA was evident. Furthermore, we utilized machine-learning algorithms to identify molecular correlates that conferred increased sensitivity to platinum and olaparib treatments including somatic mutations in BRCA1, ATM, and MYC. Conversely, patients with ALK mutation were considerably resistant to both treatment modalities. Collectively, our results demonstrate the clinical feasibility of prospective genetic sequencing to facilitate personalized treatment opportunities for patients with EOC.

Advances in pathogenesis and therapeutic strategies for osteoporosis

Osteoporosis, is the most common bone disorder worldwide characterized by low bone mineral density, leaving affected bones vulnerable to fracture. Bone homeostasis depends on the precise balance between bone resorption by osteoclasts and bone matrix formation by mesenchymal lineage osteoblasts, and involves a series of complex and highly regulated steps. Bone homeostasis will be disrupted when the speed of bone resorption is faster than bone formation. Based on various regulatory mechanisms of bone homeostasis, a series of drugs targeting osteoporosis have emerged in clinical practice, including bisphosphonates, selective estrogen receptor modulators, calcitonin, molecular-targeted drugs and so on. However, many drugs have major adverse effects or are unsuitable for long-term use. Therefore, it is very urgent to find more effective therapeutic drugs based on the new pathogenesis of osteoporosis. In this review, we summarize novel mechanisms involved in the pathological process of osteoporosis, including the roles of gut microbiome, autophagy, iron balance and cellular senescence. Based on the above pathological mechanism, we found promising drugs for osteoporosis treatment, such as: probiotics, alpha-ketoglutarate, senolytics and hydrogen sulfide. This new finding may provide an important basis for elucidating the complex pathological mechanisms of osteoporosis and provide promising drugs for clinical osteoporosis treatment.

Functional Therapeutic Target Validation Using Pediatric Zebrafish Xenograft Models

Simple Summary

Despite the major progress of precision and personalized oncology, a significant therapeutic benefit is only achieved in cases with directly druggable genetic alterations. This highlights the need for additional methods that reliably predict each individual patient’s response in a clinically meaningful time, e.g., through ex vivo functional drug screen profiling. Moreover, patient-derived xenograft (PDX) models are more predictive than cell culture studies, as they reconstruct cell–cell and cell–extracellular matrix (ECM) interactions and consider the tumor microenvironment, drug metabolism and toxicities. Zebrafish PDXs (zPDX) are nowadays emerging as a fast model allowing for multiple drugs to be tested at the same time in a clinically relevant time window. Here, we show that functional drug response profiling of zPDX from primary material obtained through the INdividualized Therapy FOr Relapsed Malignancies in Childhood (INFORM) pediatric precision oncology pipeline provides additional key information for personalized precision oncology.

Abstract

The survival rate among children with relapsed tumors remains poor, due to tumor heterogeneity, lack of directly actionable tumor drivers and multidrug resistance. Novel personalized medicine approaches tailored to each tumor are urgently needed to improve cancer treatment. Current pediatric precision oncology platforms, such as the INFORM (INdividualized Therapy FOr Relapsed Malignancies in Childhood) study, reveal that molecular profiling of tumor tissue identifies targets associated with clinical benefit in a subgroup of patients only and should be complemented with functional drug testing. In such an approach, patient-derived tumor cells are exposed to a library of approved oncological drugs in a physiological setting, e.g., in the form of animal avatars injected with patient tumor cells. We used molecularly fully characterized tumor samples from the INFORM study to compare drug screen results of individual patient-derived cell models in functional assays: (i) patient-derived spheroid cultures within a few days after tumor dissociation; (ii) tumor cells reisolated from the corresponding mouse PDX; (iii) corresponding long-term organoid-like cultures and (iv) drug evaluation with the corresponding zebrafish PDX (zPDX) model. Each model had its advantage and complemented the others for drug hit and drug combination selection. Our results provide evidence that in vivo zPDX drug screening is a promising add-on to current functional drug screening in precision medicine platforms.

Identification of Prognostic Markers of Gynecologic Cancers Utilizing Patient-Derived Xenograft Mouse Models

Patient-derived xenografts (PDXs) are important in vivo models for the development of precision medicine. However, challenges exist regarding genetic alterations and relapse after primary treatment. Thus, PDX models are required as a new approach for preclinical and clinical studies. We established PDX models of gynecologic cancers and analyzed their clinical information. We subcutaneously transplanted 207 tumor tissues from patients with gynecologic cancer into nude mice from 2014 to 2019. The successful engraftment rate of ovarian, cervical, and uterine cancer was 47%, 64%, and 56%, respectively. The subsequent passages (P2 and P3) showed higher success and faster growth rates than the first passage (P1). Using gynecologic cancer PDX models, the tumor grade is a common clinical factor affecting PDX establishment. We found that the PDX success rate correlated with the patient’s prognosis, and also that ovarian cancer patients with a poor prognosis had a faster PDX growth rate (p < 0.0001). Next, the gene sets associated with inflammation and immune responses were shown in high-ranking successful PDX engraftment through gene set enrichment analysis and RNA sequencing. Up-regulated genes in successful engraftment were found to correlate with ovarian clear cell cancer patient outcomes via Gene Expression Omnibus dataset analysis.

Research progress of PARP inhibitor monotherapy and combination therapy for endometrial cancer

Endometrial cancer is one of the three most common malignant tumors in the female reproductive system. Advanced and recurrent endometrial cancers have poor prognoses and lack effective treatments. Poly(ADP-ribose) polymerase (PARP) inhibitors have been applied to many different types of tumors, and they can selectively kill tumor cells that are defective in homologous recombination repair. Endometrial cancer is characterized by mutations in homologous recombination repair genes; accordingly, PARP inhibitors have achieved positive results in off-label treatments of endometrial cancer cases. Clinical trials of PARP inhibitors as monotherapies and within combination therapies for endometrial cancer are ongoing. For this review, we searched PubMed with "endometrial cancer" and "PARP inhibitor" as keywords, and we used "olaparib", "rucaparib", "niraparib" and "talazoparib" as search terms in clinicaltrials.gov for ongoing trials. The literature search ended in October 2020, and only English-language publications were selected. Multiple studies confirm that PARP inhibitors play an important role in killing tumor cells with defects in homologous recombination repair. Its combination with immune checkpoint inhibitors, PI3K/AKT/mTOR pathway inhibitors, cell cycle checkpoint inhibitors, and other drugs can improve the treatment of endometrial cancer.

Serous Carcinoma of the Endometrium with Mesonephric-Like Differentiation Initially Misdiagnosed as Uterine Mesonephric-Like Adenocarcinoma: A Case Report with Emphasis on the Immunostaining and the Identification of Splice Site TP53 Mutation

We present herein a rare case of uterine serous carcinoma with mesonephric-like differentiation (SC-MLD) initially misdiagnosed as mesonephric-like adenocarcinoma (MLA). A 51-year-old woman underwent total hysterectomy for a uterine tumor. Histologically, the tumor exhibited various architectures, including papillary, glandular, tubular, cribriform, and cystic. On the basis of this architectural diversity accompanied by intraluminal eosinophilic secretions and intermediate-grade nuclear atypia, the initial diagnosis was MLA. However, the tumor was diffusely and strongly positive for the expression of p16 and negative for the expression of GATA-binding protein 3 (GATA3). Furthermore, we identified a pathogenic tumor protein 53 (TP53) mutation affecting an acceptor splice site in intron 9, despite a wild-type p53 immunostaining pattern. The observations of diffuse and strong p16 expression, lack of GATA3 expression, pathogenic TP53 mutation, and wild-type Kirsten rat sarcoma viral oncogene homolog indicate that this tumor was not an MLA but an SC-MLD. Both uterine SC and MLA can exhibit various histological growth patterns. Our comprehensive clinicopathological and molecular analyses can serve to improve the understanding of this rare condition and help pathologists in making an accurate diagnosis.

Comprehensive molecular characterization of gastric cancer patients from phase II second-line ramucirumab plus paclitaxel therapy trial

BACKGROUND

Gastric cancer (GC) is a heterogenous disease consisted of several subtypes with distinct molecular traits. The clinical implication of molecular classification has been limited especially in association with treatment efficacy of ramucirumab or various targeted agents.

METHODS

We conducted a prospective non-randomized phase II single-arm trial of ramucirumab plus paclitaxel as second-line chemotherapy in 62 patients with metastatic GC who failed to respond to first-line fluoropyrimidine plus platinum treatment. For integrative molecular characterization, all patients underwent pre-ramucirumab treatment tissue biopsy for whole-exome/whole-transcriptome sequencing to categorize patients based on molecular subtypes. We also systematically performed integrative analysis, combining genomic, transcriptomic, and clinical features, to identify potential molecular predictors of sensitivity and resistance to ramucirumab treatment.

RESULTS

Sixty-two patients were enrolled in this study between May 2016 and October 2017. Survival follow-up in all patients was completed as of the date of cut-off on January 2, 2019. No patient attained complete response (CR), while 22 patients achieved confirmed partial response (PR), resulting in a response rate (RR) of 35.5% (95% CI, 23.6-47.4). According to TCGA molecular classification, there were 30 GS, 18 CIN, 3 EBV, and 0 MSI tumors. The RR was 33% in GS (10/30), 33% in CIN (6/18), and 100% in EBV-positive GC patients with significant statistical difference for EBV(+) against EBV(-) tumors (P = 0.016; chi-squared test). Moreover, responsive patients were marked by activation of angiogenesis, VEGF, and TCR-associated pathways, while non-responder patients demonstrated enrichments of sonic hedgehog signaling pathway and metabolism activity. Integrative multi-layer data analysis further identified molecular determinants, including EBV status, and somatic mutation in GNAQ to ramucirumab activity.

CONCLUSIONS

Prospective molecular characterization identified a subset of GC patients with distinct clinical response to ramucirumab therapy, and our results demonstrate the feasibility of personalized therapeutic opportunities in gastric cancer.

TRIAL REGISTRATION

The study was registered on ClinicalTrial.gov ( NCT02628951 ) on June 12, 2015.

High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma

Simple Summary

Real-time ex vivo drug testing tailors individual therapeutics based on predicted drug responses. Most technologies to date rely on conventional drug screening that provides low confidence data. Here, we present high-content analysis-based drug testing of glioblastoma patients to identify the right glioblastoma patients for a given drug. This generates multi-parameter biomarker and phenotype readouts providing a better reliability of the assay. Additionally, we showed a high-content drug repurposing screen and defined a new c-Met-inhibiting function of the CDK4/6 inhibitor Abemaciclib. Large-scale high throughput screening results demonstrate that Abemaciclib sensitivity in glioblastoma patients is highly correlated with the c-Met inhibitors sensitivity, further supporting the accuracy of the platform and important new clinical implications regarding multiple functions of Abemaciclib.

Abstract

(1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.

The Application of Patient-Derived Xenograft Models in Gynecologic Cancers

Recently, due to the limitations of cell line models and animal models in the preclinical research with insufficient reflecting the physiological situation of humans, patient-derived xenograft (PDX) models of many cancers have been widely developed because of their better representation of the tumor heterogeneity and tumor microenvironment with retention of the cellular complexity, cytogenetics, and stromal architecture. PDX models now have been identified as a powerful tool for determining cancer characteristics, developing new treatment, and predicting drug efficacy. An increase in attempts to generate PDX models in gynecologic cancers has emerged in recent years to understand tumorigenesis. Hence, this review summarized the generation of PDX models and engraftment success of PDX models in gynecologic cancers. Furthermore, we illustrated the similarity between PDX model and original tumor, and described preclinical utilization of PDX models in gynecologic cancers. It would help supply better personalized therapy for gynecologic cancer patients.

Comprehensive pharmacogenomic characterization of gastric cancer

BACKGROUND

Gastric cancer is among the most lethal human malignancies. Previous studies have identified molecular aberrations that constitute dynamic biological networks and genomic complexities of gastric tumors. However, the clinical translation of molecular-guided targeted therapy is hampered by challenges. Notably, solid tumors often harbor multiple genetic alterations, complicating the development of effective treatments.

METHODS

To address such challenges, we established a comprehensive dataset of molecularly annotated patient derivatives coupled with pharmacological profiles for 60 targeted agents to explore dynamic pharmacogenomic interactions in gastric cancers.

RESULTS

We identified lineage-specific drug sensitivities based on histopathological and molecular subclassification, including substantial sensitivities toward VEGFR and EGFR inhibition therapies in diffuse- and signet ring-type gastric tumors, respectively. We identified potential therapeutic opportunities for WNT pathway inhibitors in ALK-mutant tumors, a significant association between PIK3CA-E542K mutation and AZD5363 response, and transcriptome expression of RNF11 as a potential predictor of response to gefitinib.

CONCLUSIONS

Collectively, our results demonstrate the feasibility of drug screening combined with tumor molecular characterization to facilitate personalized therapeutic regimens for gastric tumors.