Evaluation of molecular subtypes and clonal selection during establishment of patient-derived tumor xenografts from gastric adenocarcinoma

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

BACKGROUND

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1). To address the critical need for novel therapeutics in MPNST, we aimed to establish an ex vivo 3D platform that accurately captured the genomic diversity of MPNST and could be utilized in a medium-throughput manner for drug screening studies to be validated in vivo using patient-derived xenografts (PDX).

METHODS

Genomic analysis was performed on all PDX-tumor pairs. Selected PDX were harvested for assembly into 3D microtissues. Based on prior work in our labs, we evaluated drugs (trabectedin, olaparib, and mirdametinib) ex vivo and in vivo. For 3D microtissue studies, cell viability was the endpoint as assessed by Zeiss Axio Observer. For PDX drug studies, tumor volume was measured twice weekly. Bulk RNA sequencing was performed to identify pathways enriched in cells.

RESULTS

We developed 13 NF1-associated MPNST-PDX and identified mutations or structural abnormalities in NF1 (100%), SUZ12 (85%), EED (15%), TP53 (15%), CDKN2A (85%), and chromosome 8 gain (77%). We successfully assembled PDX into 3D microtissues, categorized as robust (>90% viability at 48 h), good (>50%), or unusable (<50%). We evaluated drug response to "robust" or "good" microtissues, namely MN-2, JH-2-002, JH-2-079-c, and WU-225. Drug response ex vivo predicted drug response in vivo, and enhanced drug effects were observed in select models.

CONCLUSIONS

These data support the successful establishment of a novel 3D platform for drug discovery and MPNST biology exploration in a system representative of the human condition.

High In Vitro and In Vivo Activity of BI-847325, a Dual MEK/Aurora Kinase Inhibitor, in Human Solid and Hematologic Cancer Models

BI-847325 is an ATP-competitive inhibitor of MEK/Aurora kinases with the potential to treat a wide range of cancers. In a panel of 294 human tumor cell lines in vitro, BI-847325 was found to be a highly selective inhibitor that was active in the submicromolar range. The most sensitive cancer types were acute lymphocytic and myelocytic leukemia, melanomas, bladder, colorectal, and mammary cancers. BI-847325 showed a broader range of activity than the MEK inhibitor GDC-0623. The high efficacy of BI-847325 was associated with but not limited to cell lines with oncogenic mutations in NRAS, BRAF, and MAP2K1.The high antiproliferative activity of BI-847325 was validated in vivo using subcutaneous xenograft models. After oral administration of 80 and 40 mg/kg once weekly for 3 or 4 weeks, BI-847325 was highly active in four of five colorectal, two of two gastric, two of two mammary, and one of one pancreatic cancer models (test/control < 25%), and tumor regressions were observed in five of 11 cancer models. The treatment was well tolerated with no relevant lethality or body weight changes. In combination with capecitabine, BI-847325 displayed synergism over single-agent therapies, leading to complete remission in the triple-negative mammary model MAXFTN 401, partial regression in the colon model CXF 1103, and stasis in the gastric models GXA 3011 and GXA 3023. In conclusion, dual MEK/Aurora kinase inhibition shows remarkable potential for treating multiple types of hematologic and solid tumors. The combination with capecitabine was synergistic in colorectal, gastric, and mammary cancer.

SIGNIFICANCE

We report the preclinical evaluation of BI-847325, a MEK/Aurora kinase inhibitor. Our data demonstrate that BI-847325 has potent antitumor activity in a broad range of human solid and hematologic cancer models in vitro and in vivo and is well tolerated in animal models. It also shows synergistic effect when combined with capecitabine. These findings provide a strong rationale for further development of BI-847325 as a potential therapeutic for patients with cancer.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Integrative genomic analysis of drug resistance in MET exon 14 skipping lung cancer using patient-derived xenograft models

Background

Non-small cell lung cancer (NSCLC) driven by MET exon 14 skipping (METex14) occurs in 3-4% of NSCLC cases and defines a subset of patients with distinct characteristics. While MET targeted therapy has led to strong clinical results in METex14 patients, acquired drug resistance seemed to be unavoidable during treatment. Limited information is available regarding acquired resistance during MET targeted therapy, nor has there been any report on such patient-derived xenografts (PDXs) model facilitating the research.

Methods

We describe a patient case harboring METex14 who exhibited drug resistance after treatment with crizotinib. Subcutaneous xenografts were generated from pretreatment and post-resistance patient specimens. PDX mice were then treated with MET inhibitors (crizotinib and tepotinib) and EGFR-MET bispecific antibodies (EMB-01 and amivantamab) to evaluate their drug response in vivo. DNA and RNA sequencing analysis was performed on patient tumor specimens and matching xenografts.

Results

PDXs preserved most of the histological and molecular profiles of the parental tumors. Drug resistance to MET targeted therapy was confirmed in PDX models through in vivo drug analysis. Newly acquired MET D1228H mutations and EGFR amplificated were detected in patient-resistant tumor specimens. Although the mutations were not detected in the PDX, EGFR overexpression was observed in RNA sequencing analysis indicating possible off-target resistance through the EGFR bypass signaling pathway. As expected, EGFR-MET bispecific antibodies overcome drug resistant in the PDX model.

Conclusions

We detected a novel MET splice site deletion mutation that could lead to METex14. We also established and characterized a pair of METex14 NSCLC PDXs, including the first crizotinib resistant METex14 PDX. And dual inhibition of MET and EGFR might be a therapeutic strategy for EGFR-driven drug resistance METex14 lung cancer.

Patient-Derived Xenograft: A More Standard "Avatar" Model in Preclinical Studies of Gastric Cancer

Despite advances in diagnosis and treatment, gastric cancer remains the third most common cause of cancer-related death in humans. The establishment of relevant animal models of gastric cancer is critical for further research. Due to the complexity of the tumor microenvironment and the genetic heterogeneity of gastric cancer, the commonly used preclinical animal models fail to adequately represent clinically relevant models of gastric cancer. However, patient-derived models are able to replicate as much of the original inter-tumoral and intra-tumoral heterogeneity of gastric cancer as possible, reflecting the cellular interactions of the tumor microenvironment. In addition to implanting patient tissues or primary cells into immunodeficient mouse hosts for culture, the advent of alternative hosts such as humanized mouse hosts, zebrafish hosts, and in vitro culture modalities has also facilitated the advancement of gastric cancer research. This review highlights the current status, characteristics, interfering factors, and applications of patient-derived models that have emerged as more valuable preclinical tools for studying the progression and metastasis of gastric cancer.

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Mapping the genomic diaspora of gastric cancer

Gastric cancer (GC) is a leading contributor to global cancer incidence and mortality. Pioneering genomic studies, focusing largely on primary GCs, revealed driver alterations in genes such as ERBB2, FGFR2, TP53 and ARID1A as well as multiple molecular subtypes. However, clinical efforts targeting these alterations have produced variable results, hampered by complex co-alteration patterns in molecular profiles and intra-patient genomic heterogeneity. In this Review, we highlight foundational and translational advances in dissecting the genomic cartography of GC, including non-coding variants, epigenomic aberrations and transcriptomic alterations, and describe how these alterations interplay with environmental influences, germline factors and the tumour microenvironment. Mapping of these alterations over the GC life cycle in normal gastric tissues, metaplasia, primary carcinoma and distant metastasis will improve our understanding of biological mechanisms driving GC development and promoting cancer hallmarks. On the translational front, integrative genomic approaches are identifying diverse mechanisms of GC therapy resistance and emerging preclinical targets, enabled by technologies such as single-cell sequencing and liquid biopsies. Validating these insights will require specifically designed GC cohorts, converging multi-modal genomic data with longitudinal data on therapeutic challenges and patient outcomes. Genomic findings from these studies will facilitate 'next-generation' clinical initiatives in GC precision oncology and prevention.

Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts

PURPOSE

Comprehensive genomic profiling has defined key oncogenic drivers and distinct molecular subtypes in esophagogastric cancer; however, the number of clinically actionable alterations remains limited. To establish preclinical models for testing genomically driven therapeutic strategies, we generated and characterized a large collection of esophagogastric cancer patient-derived xenografts (PDXs).

MATERIALS AND METHODS

We established a biobank of 98 esophagogastric cancer PDX models derived from primary tumors and metastases. Clinicopathologic features of each PDX and the corresponding patient sample were annotated, including stage at diagnosis, treatment history, histology, and biomarker profile. To identify oncogenic DNA alterations, we analyzed and compared targeted sequencing performed on PDX and parent tumor pairs. We conducted xenotrials in genomically defined models with oncogenic drivers.

RESULTS

From April 2010 to June 2019, we implanted 276 patient tumors, of which 98 successfully engrafted (35.5%). This collection is enriched for PDXs derived from patients with human epidermal growth factor receptor 2-positive esophagogastric adenocarcinoma (62 models, 63%), the majority of which were refractory to standard therapies including trastuzumab. Factors positively correlating with engraftment included advanced stage, metastatic origin, intestinal-type histology, and human epidermal growth factor receptor 2-positivity. Mutations in TP53 and alterations in receptor tyrosine kinases (ERBB2 and EGFR), RAS/PI3K pathway genes, cell-cycle mediators (CDKN2A and CCNE1), and CDH1 were the predominant oncogenic drivers, recapitulating clinical tumor sequencing. We observed antitumor activity with rational combination strategies in models established from treatment-refractory disease.

CONCLUSION

The Memorial Sloan Kettering Cancer Center PDX collection recapitulates the heterogeneity of esophagogastric cancer and is a powerful resource to investigate mechanisms driving tumor progression, identify predictive biomarkers, and develop therapeutic strategies for molecularly defined subsets of esophagogastric cancer.

Challenges in genomic analysis of model systems and primary tumors of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by aggressive tumor behavior and poor prognosis. Recent next-generation sequencing (NGS)-based genomic studies have provided novel treatment modes for pancreatic cancer via the identification of cancer driver variants and molecular subtypes in PDAC. Genome-wide approaches have been extended to model systems such as patient-derived xenografts (PDXs), organoids, and cell lines for pre-clinical purposes. However, the genomic characteristics vary in the model systems, which is mainly attributed to the clonal evolution of cancer cells during their construction and culture. Moreover, fundamental limitations such as low tumor cellularity and the complex tumor microenvironment of PDAC hinder the confirmation of genomic features in the primary tumor and model systems. The occurrence of these phenomena and their associated complexities may lead to false insights into the understanding of mechanisms and dynamics in tumor tissues of patients. In this review, we describe various model systems and discuss differences in the results based on genomics and transcriptomics between primary tumors and model systems. Finally, we introduce practical strategies to improve the accuracy of genomic analysis of primary tissues and model systems.

Molecular Targets for Gastric Cancer Treatment and Future Perspectives from a Clinical and Translational Point of View

Gastric cancer is a leading cause of cancer death worldwide. Systemic treatment comprising chemotherapy and targeted therapy is the standard of care in advanced/metastatic gastric cancer. Comprehensive molecular characterization of gastric adenocarcinomas by the TCGA Consortium and ACRG has resulted in the definition of distinct molecular subtypes. These efforts have in parallel built a basis for the development of novel molecularly stratified treatment approaches. Based on this molecular characterization, an increasing number of specific genomic alterations can potentially serve as treatment targets. Consequently, the development of promising compounds is ongoing. In this review, key molecular alterations in gastric and gastroesophageal junction cancers will be addressed. Finally, the current status of the translation of targeted therapy towards clinical applications will be reviewed.

Hsa-miR-30a-3p attenuates gastric adenocarcinoma proliferation and metastasis via APBB2

Background: There is a well-established relationship between cell cycle progression and the development of stomach adenocarcinoma. This study aimed to elucidate the molecular mechanism and biological function of APBB2 in gastric cancer.

Methods: Gastric adenocarcinoma (GA) data were downloaded from the TCGA-GA and GEO databases and analyzed to explore differentially expressed miRNAs and mRNAs. Moreover, potential target mRNAs were also predicted. The relative level of gene and protein expression in GA cell lines and gastric mucosa cells was detected by q-PCR and Western blot, respectively. Moreover, the influence of APBB2 on proliferation, metastasis, and cell cycle changes in SGC-7901 and BGC-823 cells was evaluated. The binding relationship between the target miRNA and mRNA was confirmed with a dual-luciferase reporter assay.

Results: High APBB2 expression was detected in GA patients, indicating that it may be represent a predictive biomarker for poor prognosis. Related experiments confirmed that APBB2 silencing inhibited GA cellular functions, including proliferation, cell cycle progression, migration, and invasion. In addition, to explore the molecular mechanism, our results indicated that the binding sites were located at hsa-mir-30a and the 3′-UTR of APBB2, suggesting that hsa-mir-30a can regulate the expression of APBB2. The biological functions of hsa-mir-30a were also evaluated. Hsa-mir-30a overexpression attenuated the proliferation and metastasis of cancer cells. In rescue experiments, hsa-mir-30a was confirmed to reverse the cell cycle promoting function associated with APBB2 overexpression.

Conclusion: Our findings show that hsa-mir-30a can attenuate the development of GA by down-regulating APBB2 expression.