Characterization of drug responses of mini patient-derived xenografts in mice for predicting cancer patient clinical therapeutic response

USP7 depletion potentiates HIF2α degradation and inhibits clear cell renal cell carcinoma progression

Clear cell renal cell carcinoma (ccRCC) is characterized by Von Hippel Lindau (VHL) gene loss of function mutation, which leads to the accumulation of hypoxia-inducible factor 2α (HIF2α). HIF2α has been well-established as one of the major oncogenic drivers of ccRCC, however, its therapeutic targeting remains a challenge. Through an analysis of proteomic data from ccRCCs and adjacent non-tumor tissues, we herein revealed that Ubiquitin-Specific Peptidase 7 (USP7) was upregulated in tumor tissues, and its depletion by inhibitors or shRNAs caused significant suppression of tumor progression in vitro and in vivo. Mechanistically, USP7 expression is activated by the transcription factors FUBP1 and FUBP3, and it promotes tumor progression mainly by deubiquitinating and stabilizing HIF2α. Moreover, the combination of USP7 inhibitors and afatinib (an ERBB family inhibitor) coordinately induce cell death and tumor suppression. In mechanism, afatinib indirectly inhibits USP7 transcription and accelerates the degradation of HIF2α protein, and the combination of them caused a more profound suppression of HIF2α abundance. These findings reveal a FUBPs-USP7-HIF2α regulatory axis that underlies the progression of ccRCC and provides a rationale for therapeutic targeting of oncogenic HIF2α via combinational treatment of USP7 inhibitor and afatinib.

Cancer Patient-Derived Cell-Based Models: Applications and Challenges in Functional Precision Medicine

The field of oncology has witnessed remarkable progress in personalized cancer therapy. Functional precision medicine has emerged as a promising avenue for achieving superior treatment outcomes by integrating omics profiling and sensitivity testing of patient-derived cancer cells. This review paper provides an in-depth analysis of the evolution of cancer-directed drugs, resistance mechanisms, and the role of functional precision medicine platforms in revolutionizing individualized treatment strategies. Using two-dimensional (2D) and three-dimensional (3D) cell cultures, patient-derived xenograft (PDX) models, and advanced functional assays has significantly improved our understanding of tumor behavior and drug response. This progress will lead to identifying more effective treatments for more patients. Considering the limited eligibility of patients based on a genome-targeted approach for receiving targeted therapy, functional precision medicine provides unprecedented opportunities for customizing medical interventions according to individual patient traits and individual drug responses. This review delineates the current landscape, explores limitations, and presents future perspectives to inspire ongoing advancements in functional precision medicine for personalized cancer therapy.

Amelanotic primary cervical malignant melanoma: A case report and review of literature

BACKGROUND

Primary malignant melanoma of the cervix (PMMC) is an extremely rare disease that originates from primary cervical malignant melanoma and frequently represents a challenge in disease diagnosis due to unclarified clinical and histological presentations, particularly those without melanin.

CASE SUMMARY

Here, we report a case of amelanotic PMMC, with a history of breast cancer and thyroid carcinoma. The patient was finally diagnosed by immunohistochemical staining and staged as IB2 based on the International Federation of Gynecology and Obstetrics with reference to National Comprehensive Cancer Network guidelines and was treated with radical hysterectomy, bilateral salpingo-oophorectomy and pelvic lymphadenectomy. She then received combination therapy consisting of immunotherapy with tislelizumab and radiofrequency hyperthermia. She has remained free of disease for more than 1 year.

CONCLUSION

The differential diagnosis process reenforced the notion that immunohistochemical staining is the most reliable approach for amelanotic PMMC diagnosis. Due to the lack of established therapeutic guidelines, empirical information from limited available studies does not provide the rationale for treatment-decision making. By integrating 'omics' technologies and patient-derived xenografts or mini-patient-derived xenograft models this will help to identify selective therapeutic window(s) and screen the appropriate therapeutics for targeted therapies, immune checkpoint blockade or combination therapy strategies effectively and precisely that will ultimately improve patient survival.

Gedatolisib shows superior potency and efficacy versus single-node PI3K/AKT/mTOR inhibitors in breast cancer models

The PI3K, AKT, and mTOR (PAM) pathway is frequently dysregulated in breast cancer (BC) to accommodate high catabolic and anabolic activities driving tumor growth. Current therapeutic options for patients with hormone receptor (HR) + / HER2- advanced BC (ABC) include PAM inhibitors that selectively inhibit only one PAM pathway node, which can lead to drug resistance as cells rapidly adapt to maintain viability. We hypothesized that gedatolisib, which potently inhibits all Class I PI3K isoforms, as well as mTORC1 and mTORC2, may be more effective in BC cells than single-node PAM inhibitors by limiting adaptive resistances. By using multiple functional assays, a panel of BC cell lines was evaluated for their sensitivity to four different PAM inhibitors: gedatolisib (pan-PI3K/mTOR inhibitor), alpelisib (PI3Kα inhibitor), capivasertib (AKT inhibitor), and everolimus (mTORC1 inhibitor). Gedatolisib exhibited more potent and efficacious anti-proliferative and cytotoxic effects regardless of the PAM pathway mutational status of the cell lines compared to the single-node PAM inhibitors. The higher efficacy of gedatolisib was confirmed in three-dimensional culture and in BC PDX models. Mechanistically, gedatolisib decreased cell survival, DNA replication, cell migration and invasion, protein synthesis, glucose consumption, lactate production, and oxygen consumption more effectively than the other PAM inhibitors tested. These results indicate that inhibition of multiple PAM pathway nodes by a pan-PI3K/mTOR inhibitor like gedatolisib may be more effective at inducing anti-tumor activity than single-node PAM inhibitors. A global Phase 3 study is currently evaluating gedatolisib plus fulvestrant with and without palbociclib in patients with HR+/HER2- ABC.

Development of a PAK4-targeting PROTAC for renal carcinoma therapy: concurrent inhibition of cancer cell proliferation and enhancement of immune cell response

BACKGROUND

Finding the oncogene, which was able to inhibit tumor cells intrinsically and improve the immune answers, will be the future direction for renal cancer combined treatment. Following patient sample analysis and signaling pathway examination, we propose p21-activated kinase 4 (PAK4) as a potential target drug for kidney cancer. PAK4 exhibits high expression levels in patient samples and plays a regulatory role in the immune microenvironment.

METHODS

Utilizing AI software for peptide drug design, we have engineered a specialized peptide proteolysis targeting chimera (PROTAC) drug with selectivity for PAK4. To address challenges related to drug delivery, we developed a nano-selenium delivery system for efficient transport of the peptide PROTAC drug, termed PpD (PAK4 peptide degrader).

FINDINGS

We successfully designed a peptide PROTAC drug targeting PAK4. PpD effectively degraded PAK4 with high selectivity, avoiding interference with other homologous proteins. PpD significantly attenuated renal carcinoma proliferation in vitro and in vivo. Notably, PpD demonstrated a significant inhibitory effect on tumor proliferation in a fully immunocompetent mouse model, concomitantly enhancing the immune cell response. Moreover, PpD demonstrated promising tumor growth inhibitory effects in mini-PDX and PDO models, further underscoring its potential for clinical application.

INTERPRETATION

This PAK4-targeting peptide PROTAC drug not only curtails renal cancer cell proliferation but also improves the immune microenvironment and enhances immune response. Our study paves the way for innovative targeted therapies in the management of renal cancer.

FUNDING

This work is supported by Research grants from non-profit organizations, as stated in the Acknowledgments.

FBXO22 is a potential therapeutic target for recurrent chondrosarcoma

Chondrosarcoma (CHS) is a malignant bone tumor with insensitivity to both radiotherapy and chemotherapy, and a high recurrence rate. However, the latent mechanism of recurrent CHS (Re-CHS) remains elusive. Here, we discovered that FBXO22 was highly expressed in clinical samples of Re-CHS. FBXO22 played a significant role in various cancers. However, the role of FBXO22 in Re-CHS remained unclear. Our research demonstrated that suppressing FBXO22 abated the proliferation and migration of CHS cells and facilitated their apoptosis. In addition, suppressing FBXO22 raised the expression of PD-L1 in Re-CHS. All these findings provide new evidence for using FBXO22 and PD-L1 as combined targets to prevent and treat Re-CHS, which may prove to be a novel strategy for immunotherapy of CHS, especially Re-CHS.

Genetic interactions reveal distinct biological and therapeutic implications in breast cancer

Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

Xenograft and organoid models in developing precision medicine for gastric cancer (Review)

Gastric cancer (GC), a highly heterogeneous disease, has diverse histological and molecular subtypes. For precision medicine, well‑characterized models encompassing the full spectrum of subtypes are necessary. Patient‑derived tumor xenografts and organoids serve as important preclinical models in GC research. The main advantage of these models is the retention of phenotypic and genotypic heterogeneity present in parental tumor tissues. Utilizing diverse sequencing techniques and preclinical models for GC research facilitates accuracy in predicting personalized clinical responses to anti‑cancer treatments. The present review summarizes the latest advances of these two preclinical models in GC treatment and drug response assessment.

Ex-vivo drug screening of surgically resected glioma stem cells to replace murine avatars and provide personalise cancer therapy for glioblastoma patients

With diminishing returns and high clinical failure rates from traditional preclinical and animal-based drug discovery strategies, more emphasis is being placed on alternative drug discovery platforms. Ex vivo approaches represent a departure from both more traditional preclinical animal-based models and clinical-based strategies and aim to address intra-tumoural and inter-patient variability at an earlier stage of drug discovery. Additionally, these approaches could also offer precise treatment stratification for patients within a week of tumour resection in order to direct tailored therapy. One tumour group that could significantly benefit from such ex vivo approaches are high-grade gliomas, which exhibit extensive heterogeneity, cellular plasticity and therapy-resistant glioma stem cell (GSC) niches. Historic use of murine-based preclinical models for these tumours has largely failed to generate new therapies, resulting in relatively stagnant and unacceptable survival rates of around 12-15 months post-diagnosis over the last 50 years. The near universal use of DNA damaging chemoradiotherapy after surgical resection within standard-of-care (SoC) therapy regimens provides an opportunity to improve current treatments if we can identify efficient drug combinations in preclinical models that better reflect the complex inter-/intra-tumour heterogeneity, GSC plasticity and inherent DNA damage resistance mechanisms. We have therefore developed and optimised a high-throughput ex vivo drug screening platform; GliExP, which maintains GSC populations using immediately dissociated fresh surgical tissue. As a proof-of-concept for GliExP, we have optimised SoC therapy responses and screened 30+ small molecule therapeutics and preclinical compounds against tumours from 18 different patients, including multi-region spatial heterogeneity sampling from several individual tumours. Our data therefore provides a strong basis to build upon GliExP to incorporate combination-based oncology therapeutics in tandem with SoC therapies as an important preclinical alternative to murine models (reduction and replacement) to triage experimental therapeutics for clinical translation and deliver rapid identification of effective treatment strategies for individual gliomas.

MYC induces CDK4/6 inhibitors resistance by promoting pRB1 degradation

CDK4/6 inhibitors (CDK4/6i) show anticancer activity in certain human malignancies, such as breast cancer. However, their application to other tumor types and intrinsic resistance mechanisms are still unclear. Here, we demonstrate that MYC amplification confers resistance to CDK4/6i in bladder, prostate and breast cancer cells. Mechanistically, MYC binds to the promoter of the E3 ubiquitin ligase KLHL42 and enhances its transcription, leading to RB1 deficiency by inducing both phosphorylated and total pRB1 ubiquitination and degradation. We identify a compound that degrades MYC, A80.2HCl, which induces MYC degradation at nanomolar concentrations, restores pRB1 protein levels and re-establish sensitivity of MYC high-expressing cancer cells to CDK4/6i. The combination of CDK4/6i and A80.2HCl result in marked regression in tumor growth in vivo. Altogether, these results reveal the molecular mechanisms underlying MYC-induced resistance to CDK4/6i and suggest the utilization of the MYC degrading molecule A80.2HCl to potentiate the therapeutic efficacy of CDK4/6i.

Fucoxanthin Inhibits Development of Sigmoid Colorectal Cancer in a PDX Model With Alterations of Growth, Adhesion, and Cell Cycle Signals

BACKGROUND/AIM

Fucoxanthin (Fx), a dietary marine xanthophyll, exerts potent anticancer effects in various colorectal cancer (CRC) animal models. However, therapeutic effects of Fx in human cancer tissues remain unclear. A patient-derived xenograft (PDX) mouse model transplanted with cancer tissues from patients is widely accepted as the best preclinical model for evaluating the anticancer potential of drug candidates.

MATERIALS AND METHODS

Herein, we investigated the anticancer effects of Fx in PDX mice transplanted with cancer tissues derived from a patient with CRC (CRC-PDX) using LC-MS/MS- and western blot-based proteome analysis.

RESULTS

The tumor in the patient with CRC was a primary adenocarcinoma (T3N0M0, stage II) showing mutations of certain genes that were tumor protein p53 (TP53), AT-rich interaction domain 1A (ARID1A), neuroblastoma RAS viral oncogene homolog (NRAS), and PMS1 homolog 2 (PMS2). Administration of Fx significantly suppressed the tumor growth (0.6-fold) and tended to induce differentiation in CRC-PDX mice. Fx up-regulated glycanated-decorin (Gc-DCN) expression, and down-regulated Kinetochore-associated protein DSN1 homolog (DSN1), phospho(p) focal adhesion kinase (pFAK)(Tyr397), pPaxillin(Tyr31), and c-MYC involved in growth, adhesion, and/or cell cycle, in the tumors of CRC-PDX mice than in control mice. Alterations in the five proteins were consistent with those in human CRC HT-29 and HCT116 cells treated with fucoxanthinol (FxOH, a major metabolite of Fx).

CONCLUSION

Fx suppresses development of human-like CRC tissues, especially through growth, adhesion, and cell cycle signals.

Multiomics of HER2-low triple-negative breast cancer identifies a receptor tyrosine kinase-relevant subgroup with therapeutic prospects

To provide complementary information and reveal the molecular characteristics and therapeutic insights of HER2-low breast cancer, we performed this multiomics study of hormone receptor-negative (HR-) and HER2-low breast cancer, also known as HER2-low triple-negative breast cancer (TNBC), and identified 3 subgroups: basal-like, receptor tyrosine kinase-relevant (TKR), and mesenchymal stem-like. These 3 subgroups had distinct features and potential therapeutic targets and were validated in external data sets. Interestingly, the TKR subgroup (which exists in both HR+ and HR- breast cancer) had activated HER2 and downstream MAPK signaling. In vitro and in vivo patient-derived xenograft experiments revealed that pretreatment of the TKR subgroup with a tyrosine kinase inhibitor (lapatinib or tucatinib) could inhibit HER2 signaling and induce accumulated expression of nonfunctional HER2, resulting in increased sensitivity to the sequential HER2-targeting, Ab-drug conjugate DS-8201. Our findings identify clinically relevant subgroups and provide potential therapeutic strategies for HER2-low TNBC subtypes.

Establishment and characterization of a non-gestational choriocarcinoma patient-derived xenograft model

BACKGROUND

Non-gestational choriocarcinoma (NGC) is a rare subtype of malignant germ cell tumour and there is no consensus on its treatment. The lack of suitable preclinical models for NGC is a challenge in drug discovery research. Patient-derived xenograft (PDX) models recapitulate the tumour microenvironment of the original cancer tissue. Therefore, they have received considerable attention for studies on rare cancer. Here, we aimed to establish a PDX model from a patient with recurrent NGC.

METHODS

Fresh NGC tumour tissue was immediately transplanted into a severely immune-deficient mouse (NOD.Cg-Prkdcscid1l2rgtm1Wjl/SzJ) and maintained for more than three in vivo passages. Subsequently, we evaluated the molecular characteristics of the PDX model using immunohistochemistry, polymerase chain reaction, and RNA sequencing. Moreover, the PDX tumours were transplanted into BALB/c nude mice, and we evaluated their sensitivity for cisplatin and methotrexate.

RESULTS

The PDX tumour maintained the morphological features of NGC. Moreover, Immunohistochemistry revealed that the human chorionic gonadotropin, cytokeratin 7, and EpCAM expression levels were similar to those in the primary tumour. Furthermore, serum human chorionic gonadotropin levels were elevated in both the primary tumour and the PDX models. Additionally, using PCR analysis with species-specific primers, we confirmed that the PDX tumour contained human genes and was derived from human tissue. Moreover, the gene expression profile of the NGC was compared with that of epithelial ovarian cancer samples and cell lines, and 568 dysregulated genes in the NGC were extracted. The expression of the dysregulated genes in PDX was significantly correlated with that in the primary tumour (R2 = 0.873, P < 0.001). Finally, we demonstrated that the PDX tumour was sensitive to cisplatin and methotrexate; therefore, its clinical response to the agents was similar to that of the primary tumour.

CONCLUSIONS

We successfully established a PDX model of NGC, to the best of our knowledge, for the first time. The established PDX retained the molecular and transcriptome characteristics of the primary tumour and can be used to predict drug effects. It may facilitate further research and the development of novel therapeutic agents for NGC.

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

TERT accelerates BRAF mutant-induced thyroid cancer dedifferentiation and progression by regulating ribosome biogenesis

TERT reactivation occurs frequently in human malignancies, especially advanced cancers. However, in vivo functions of TERT reactivation in cancer progression and the underlying mechanism are not fully understood. In this study, we expressed TERT and/or active BRAF (BRAF V600E) specifically in mouse thyroid epithelium. While BRAF V600E alone induced papillary thyroid cancer (PTC), coexpression of BRAF V600E and TERT resulted in poorly differentiated thyroid carcinoma (PDTC). Spatial transcriptome analysis revealed that tumors from mice coexpressing BRAF V600E and TERT were highly heterogeneous, and cell dedifferentiation was positively correlated with ribosomal biogenesis. Mechanistically, TERT boosted ribosomal RNA (rRNA) expression and protein synthesis by interacting with multiple proteins involved in ribosomal biogenesis. Furthermore, we found that CX-5461, an rRNA transcription inhibitor, effectively blocked proliferation and induced redifferentiation of thyroid cancer. Thus, TERT promotes thyroid cancer progression by inducing cancer cell dedifferentiation, and ribosome inhibition represents a potential strategy to treat TERT-reactivated cancers.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer

Mass spectrometry (MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Data-independent acquisition (DIA) mode is considered to perform better than data-dependent acquisition (DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft (MiniPDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients. Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases. Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer (CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and MiniPDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.

OncoVee™-MiniPDX-guided anticancer treatment for HER2-negative intermediate-advanced gastric cancer patients: a single-arm, open-label phase I clinical study

BACKGROUND

Chemotherapy is the main treatment strategy for patients with advanced HER2-negative gastric cancer (GC); yet, many patients do not respond well to treatment. This study evaluated the sensitivity of a mini patient-derived xenograft (MiniPDX) animal model in patients with HER2-negative intermediate-advanced GC.

METHODS

In this single-arm, open-label clinical study, we consecutively recruited patients with HER2-negative advanced or recurrent GC from September 2018 to July 2021. Tumor tissues were subjected to MiniPDX drug sensitivity tests for screening individualized anti-tumor drugs; appropriate drug types or combinations were selected based on drug screening results. The primary endpoints were progression-free survival (PFS) and safety, and the secondary endpoints were overall survival (OS) and objective response rate (ORR).

RESULTS

A total of 17 patients were screened, and 14 eligible patients were included.The median follow-up time was 9 (2-34) months. The median PFS time was 14.1 (2-34) months, the median OS time was 16.9 (2-34) months, ORR was 42.9% (6/14), and DCR was 92.9% (13/14). The most common treatment-related adverse events (TRAE) were fatigue (14 (100%)), anorexia (13 (93%)) and insomnia (12 (86%)), and the most common grade 3 or worse TRAE was fatigue (6 (43%)), and anorexia (6 (43%)). The occurrence rate of myelosuppression, nausea and vomiting, abnormal liver enzymes, and other grade 3-4 chemotherapy adverse reactions were relatively low, and no grade 5 treatment-related adverse events occurred.

CONCLUSION

Screening HER2-negative medium-advanced GC/GJC chemotherapy regimens and targeted drugs based on MiniPDX animal models showed good tumor activity and safety.

Patient-derived organoids in translational oncology and drug screening

Patient-derived organoids (PDO) are a new biomedical research model that can reconstruct phenotypic and genetic characteristics of the original tissue and are useful for research on pathogenesis and drug screening. To introduce the progression in this field, we review the key factors of constructing organoids derived from epithelial tissues and cancers, covering culture medium and matrix, morphological characteristics, genetic profiles, high-throughput drug screening, and application potential. We also discuss the co-culture system of cancer organoids with tumor microenvironment (TME) associated cells. The co-culture system is widely used in evaluating crosstalk of cancer cells with TME components, such as fibroblasts, endothelial cells, immune cells, and microorganisms. The article provides a prospective for standardized cultivation mode, automatic morphological evaluation, and drug sensitivity screening using high-throughput methods.

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.

Experimental mouse models for translational human cancer research

The development and growth of tumors remains an important and ongoing threat to human life around the world. While advanced therapeutic strategies such as immune checkpoint therapy and CAR-T have achieved astonishing progress in the treatment of both solid and hematological malignancies, the malignant initiation and progression of cancer remains a controversial issue, and further research is urgently required. The experimental animal model not only has great advantages in simulating the occurrence, development, and malignant transformation mechanisms of tumors, but also can be used to evaluate the therapeutic effects of a diverse array of clinical interventions, gradually becoming an indispensable method for cancer research. In this paper, we have reviewed recent research progress in relation to mouse and rat models, focusing on spontaneous, induced, transgenic, and transplantable tumor models, to help guide the future study of malignant mechanisms and tumor prevention.

MiR-7-5p/KLF4 signaling inhibits stemness and radioresistance in colorectal cancer

Resistance to radiotherapy remains a major unmet clinical obstacle in the treatment of locally advanced rectal cancer. Cancer stem cells (CSCs) are considered to mediate tumor development and radioresistance. However, the role of CSCs in regulating resistance to radiotherapy in colorectal cancer (CRC) remains largely unknown. We established two radioresistant CRC cell lines, HCT116-R and RKO-R, using fractionated irradiation. Analysis using miRNA sequencing and quantitative real-time PCR confirmed lower levels of miR-7-5p in both of the radioresistant cells compared to their parental cells. Subsequently, we validated that miR-7-5p expression was decreased in cancerous tissues from radiotherapy-resistant rectal cancer patients. The Cancer Genome Atlas (TCGA) database analyses revealed that low miR-7-5p expression was significantly correlated with poor prognosis in CRC patients. Overexpression of miR-7-5p led to a rescue of radioresistance and an increase in radiation-induced apoptosis, and attenuated the stem cell-like properties in HCT116-R and RKO-R cells. Conversely, knocking down miR-7-5p in parental HCT116 and RKO cells suppressed the sensitivity to radiation treatment and enhance cancer cell stemness. Stemness-associated transcription factor KLF4 was demonstrated as a target of miR-7-5p. Rescue experiments revealed that miR-7-5p/KLF4 axis could induce radiosensitivity by regulating CSCs in colorectal cancer cells. Furthermore, we used CRC tumor tissues which exhibited resistance to neoadjuvant radiotherapy to establish a patient-derived xenograft (PDX) mouse model. Tail vein injection of magnetic nanoparticles carrying miR-7-5p mimics into the PDX mice significantly inhibited tumor growth with or without irradiation treatment in vivo. Our current studies not only demonstrate an anti-cancer function of miR-7-5p in regulating CSC properties and radiosensitivity in colorectal cancer, but also provide a novel potential strategy for delaying or reverse radiation resistance in preoperative radiotherapy of CRC patients.

Translation Potential and Challenges of In Vitro and Murine Models in Cancer Clinic

As one of the leading causes of death from disease, cancer continues to pose a serious threat to human health globally. Despite the development of novel therapeutic regimens and drugs, the long-term survival of cancer patients is still very low, especially for those whose diagnosis is not caught early enough. Meanwhile, our understanding of tumorigenesis is still limited. Suitable research models are essential tools for exploring cancer mechanisms and treatments. Herein we review and compare several widely used in vitro and in vivo murine cancer models, including syngeneic tumor models, genetically engineered mouse models (GEMM), cell line-derived xenografts (CDX), patient-derived xenografts (PDX), conditionally reprogrammed (CR) cells, organoids, and MiniPDX. We will summarize the methodology and feasibility of various models in terms of their advantages and limitations in the application prospects for drug discovery and development and precision medicine.

Advances in the Lung Cancer Immunotherapy Approaches

Despite the progress in the comprehension of LC progression, risk, immunologic control, and treatment choices, it is still the primary cause of cancer-related death. LC cells possess a very low and heterogeneous antigenicity, which allows them to passively evade the anticancer defense of the immune system by educating cytotoxic lymphocytes (CTLs), tumor-infiltrating lymphocytes (TILs), regulatory T cells (Treg), immune checkpoint inhibitors (ICIs), and myeloid-derived suppressor cells (MDSCs). Though ICIs are an important candidate in first-line therapy, consolidation therapy, adjuvant therapy, and other combination therapies involving traditional therapies, the need for new predictive immunotherapy biomarkers remains. Furthermore, ICI-induced resistance after an initial response makes it vital to seek and exploit new targets to benefit greatly from immunotherapy. As ICIs, tumor mutation burden (TMB), and microsatellite instability (MSI) are not ideal LC predictive markers, a multi-parameter analysis of the immune system considering tumor, stroma, and beyond can be the future-oriented predictive marker. The optimal patient selection with a proper adjuvant agent in immunotherapy approaches needs to be still revised. Here, we summarize advances in LC immunotherapy approaches with their clinical and preclinical trials considering cancer models and vaccines and the potential of employing immunology to predict immunotherapy effectiveness in cancer patients and address the viewpoints on future directions. We conclude that the field of lung cancer therapeutics can benefit from the use of combination strategies but with comprehension of their limitations and improvements.

TreeQNet: a webserver for Treatment evaluation with Quantified Network

Background

Personalized therapy has been at the forefront of cancer care, making cancer treatment more effective. Since cancer patients respond individually to drug therapy, predicting the sensitivity of each patient to specific drugs is very helpful to apply therapeutic agents. Traditional methods focus on node (molecular) information but ignore relevant interactions among different nodes, which has very limited application in complex situations, such as cancer drug responses in real clinical practice.

Results

Treatment evaluation with Quantified Network (TreeQNet) is a webserver which could predict sensitivity to drugs for patients through the innovative use of proteomic and phosphoproteomic network from tumor tissues.

Conclusion

TreeQNet service: http://bioinfo.ustc.edu.cn/. TreeQNet source code: https://github.com/Really00/treeqnet-web-front/.

Precision oncology using ex vivo technology: a step towards individualised cancer care?

Despite advances in cancer genomics and the increased use of genomic medicine, metastatic cancer is still mostly an incurable and fatal disease. With diminishing returns from traditional drug discovery strategies, and high clinical failure rates, more emphasis is being placed on alternative drug discovery platforms, such as ex vivo approaches. Ex vivo approaches aim to embed biological relevance and inter-patient variability at an earlier stage of drug discovery, and to offer more precise treatment stratification for patients. However, these techniques also have a high potential to offer personalised therapies to patients, complementing and enhancing genomic medicine. Although an array of approaches are available to researchers, only a minority of techniques have made it through to direct patient treatment within robust clinical trials. Within this review, we discuss the current challenges to ex vivo approaches within clinical practice and summarise the contemporary literature which has directed patient treatment. Finally, we map out how ex vivo approaches could transition from a small-scale, predominantly research based technology to a robust and validated predictive tool. In future, these pre-clinical approaches may be integrated into clinical cancer pathways to assist in the personalisation of therapy choices and to hopefully improve patient experiences and outcomes.

Prediction the clinical EPR effect of nanoparticles in patient-derived xenograft models

Many preclinically tested nanoparticles in existing animal models fail to be directly translated into clinical applications because of their poor resemblance to human cancer. Herein, the enhanced permeation and retention (EPR) effect of glycol chitosan nanoparticles (CNPs) in different tumor microenvironments (TMEs) was compared using different pancreatic tumor models, including pancreatic cancer cell line (BxPC3), patient-derived cancer cell (PDC), and patient-derived xenograft (PDX) models. CNPs were intravenously injected into different tumor models, and their accumulation efficiency was evaluated using non-invasive near-infrared fluorescence (NIRF) imaging. In particular, differences in angiogenic vessel density, collagen matrix, and hyaluronic acid content in tumor tissues of the BxPC3, PDC, and PDX models greatly affected the tumor-targeting efficiency of CNPs. In addition, different PDX models were established using different tumor tissues of patients to predict the clinical EPR effect of CNPs in inter-patient TMEs, wherein the gene expression levels of PECAM1, COL4A1, and HAS1 in human tumor tissues were observed to be closely related to the EPR effect of CNPs in PDX models. The results suggested that the PDX models could mimic inter-patient TMEs with different blood vessel structures and extracellular matrix (ECM) content that critically affect the tumor-targeting ability of CNPs in different pancreatic PDX models. This study provides a better understanding of the heterogeneity and complexity of inter-patient TMEs that can predict the response of various nanoparticles in individual tumors for personalized cancer therapy.

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.

Endometrial Cancer Patient-Derived Xenograft Models: A Systematic Review

BACKGROUND

Because patient-derived xenograft (PDX) models resemble the original tumors, they can be used as platforms to find target agents for precision medicine and to study characteristics of tumor biology such as clonal evolution and microenvironment interactions. The aim of this review was to identify articles on endometrial cancer PDXs (EC-PDXs) and verify the methodology and outcomes.

METHODS

We used PubMed to research and identify articles on EC-PDX. The data were analyzed descriptively.

RESULTS

Post literature review, eight studies were selected for the systematic review. Eighty-five EC-PDXs were established from 173 patients with EC, with a total success rate of 49.1%. A 1-10 mm3 fragment was usually implanted. Fresh-fragment implantation had higher success rates than using overnight-stored or frozen fragments. Primary tumors were successfully established with subcutaneous implantation, but metastasis rarely occurred; orthotopic implantation via minced tumor cell injection was better for metastatic models. The success rate did not correspond to immunodeficiency grades, and PDXs using nude mice reduced costs. The tumor growth period ranged from 2 weeks to 13 months. Similar characteristics were observed between primary tumors and PDXs, including pathological findings, gene mutations, and gene expression.

CONCLUSION

EC-PDXs are promising tools for translational research because they closely resemble the features of tumors in patients and retain molecular and histological features of the disease.

Monitoring and modulation of the tumor microenvironment for enhanced cancer modeling

Cancer treatments utilizing biologic or cytotoxic drugs compose the frontline of therapy, and though gains in treatment efficacy have been persistent in recent decades, much work remains in understanding cancer progression and treatment. Compounding this situation is the low rate of success when translating preclinical drug candidates to the clinic, which raises costs and development timelines. This underperformance is due in part to the poor recapitulation of the tumor microenvironment, a critical component of cancer biology, in cancer model systems. New technologies capable of both accurately observing and manipulating the tumor microenvironment are needed to effectively model cancer response to treatment. In this review, conventional cancer models are summarized, and a primer on emerging techniques for monitoring and modulating the tumor microenvironment is presented and discussed.

In vitrobreast cancer model with patient-specific morphological features for personalized medicine

In vitro cancer models that can simulate patient-specific drug responses for personalized medicine have attracted significant attention. However, the technologies used to produce such models can only recapitulate the morphological heterogeneity of human cancer tissue. Here, we developed a novel 3D technique to bioprint an in vitro breast cancer model with patient-specific morphological features. This model can precisely mimic the cellular microstructures of heterogeneous cancer tissues and produce drug responses similar to those of human cancers. We established a bioprinting process for generating cancer cell aggregates with ductal and solid tissue microstructures that reflected the morphology of breast cancer tissues, and applied it to develop breast cancer models. The genotypic and phenotypic characteristics of the ductal and solid cancer aggregates bioprinted with human breast cancer cells (MCF7, SKBR3, MDA-MB-231) were respectively similar to those of early and advanced cancers. The bioprinted solid cancer cell aggregates showed significantly higher hypoxia (>8 times) and mesenchymal (>2-4 times) marker expressions, invasion activity (>15 times), and drug resistance than the bioprinted ductal aggregates. Co-printing the ductal and solid aggregates produced heterogeneous breast cancer tissue models that recapitulated three different stages of breast cancer tissue morphology. The bioprinted cancer tissue models representing advanced cancer were more and less resistant, respectively, to the anthracycline antibiotic doxorubicin and the hypoxia-activated prodrug tirapazamine; these were analogous to the results in human cancer. The present findings showed that cancer cell aggregates can mimic the pathological micromorphology of human breast cancer tissue and they can be bioprinted to produce breast cancer tissue in vitro that can morphologically represent the clinical stage of cancer in individual patients.

Multicellular Modelling of Difficult-to-Treat Gastrointestinal Cancers: Current Possibilities and Challenges

Cancers affecting the gastrointestinal system are highly prevalent and their incidence is still increasing. Among them, gastric and pancreatic cancers have a dismal prognosis (survival of 5–20%) and are defined as difficult-to-treat cancers. This reflects the urge for novel therapeutic targets and aims for personalised therapies. As a prerequisite for identifying targets and test therapeutic interventions, the development of well-established, translational and reliable preclinical research models is instrumental. This review discusses the development, advantages and limitations of both patient-derived organoids (PDO) and patient-derived xenografts (PDX) for gastric and pancreatic ductal adenocarcinoma (PDAC). First and next generation multicellular PDO/PDX models are believed to faithfully generate a patient-specific avatar in a preclinical setting, opening novel therapeutic directions for these difficult-to-treat cancers. Excitingly, future opportunities such as PDO co-cultures with immune or stromal cells, organoid-on-a-chip models and humanised PDXs are the basis of a completely new area, offering close-to-human models. These tools can be exploited to understand cancer heterogeneity, which is indispensable to pave the way towards more tumour-specific therapies and, with that, better survival for patients.

Opportunities and challenges of patient-derived models in cancer research: patient-derived xenografts, patient-derived organoid and patient-derived cells

Background

As reported, preclinical animal models differ greatly from the human body. The evaluation model may be the colossal obstacle for scientific research and anticancer drug development. Therefore, it is essential to propose efficient evaluation systems similar to clinical practice for cancer research.

Main body

While it has emerged for decades, the development of patient-derived xenografts, patient-derived organoid and patient-derived cell used to be limited. As the requirements for anticancer drug evaluation increases, patient-derived models developed rapidly recently, which is widely applied in basic research, drug development, and clinical application and achieved remarkable progress. However, there still lack systematic comparison and summarize reports for patient-derived models. In the current review, the development, applications, strengths, and challenges of patient-derived models in cancer research were characterized.

Conclusion

Patient-derived models are an indispensable approach for cancer research and human health.

Copy number amplification of ENSA promotes the progression of triple-negative breast cancer via cholesterol biosynthesis

Copy number alterations (CNAs) are pivotal genetic events in triple-negative breast cancer (TNBC). Here, our integrated copy number and transcriptome analysis of 302 TNBC patients reveals that gene alpha-endosulfine (ENSA) exhibits recurrent amplification at the 1q21.3 region and is highly expressed in TNBC. ENSA promotes tumor growth and indicates poor patient survival in TNBC. Mechanistically, we identify ENSA as an essential regulator of cholesterol biosynthesis in TNBC that upregulates the expression of sterol regulatory element-binding transcription factor 2 (SREBP2), a pivotal transcription factor in cholesterol biosynthesis. We confirm that ENSA can increase the level of p-STAT3 (Tyr705) and activated STAT3 binds to the promoter of SREBP2 to promote its transcription. Furthermore, we reveal the efficacy of STAT3 inhibitor Stattic in TNBC with high ENSA expression. In conclusion, the amplification of ENSA at the 1q21.3 region promotes TNBC progression and indicates sensitivity to STAT3 inhibitors.

Copy number alterations are pivotal genetic events in triple-negative breast cancer. Here the authors show the amplification of ENSA at the 1q21.3 region promotes the progression of TNBC via up-regulation of cholesterol biosynthesis.

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.

Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

Patient-derived xenograft models in hepatopancreatobiliary cancer

Animal models are crucial tools for evaluating the biological progress of human cancers and for the preclinical investigation of anticancer drugs and cancer prevention. Various animals are widely used in hepatopancreatobiliary cancer research, and mouse models are the most popular. Generally, genetic tools, graft transplantation, and chemical and physical measures are adopted to generate sundry mouse models of hepatopancreatobiliary cancer. Graft transplantation is commonly used to study tumour progression. Over the past few decades, subcutaneous or orthotopic cell-derived tumour xenograft models (CDX models) have been developed to simulate distinct tumours in patients. However, two major limitations exist in CDX models. One model poorly simulates the microenvironment of tumours in humans, such as the vascular, lymphatic and immune environments. The other model loses genetic heterogeneity compared with the corresponding primary tumour. Increased efforts have focused on developing better models for hepatopancreatobiliary cancer research. Hepatopancreatobiliary cancer is considered a tumour with high molecular heterogeneity, making precision medicine challenging in cancer treatment. Developing a new animal model that can better mimic tumour tissue and more accurately predict the efficacy of anticancer treatments is urgent. For the past several years, the patient-derived xenograft model (PDX model) has emerged as a promising tool for translational research. It can retain the genetic and histological stability of their originating tumour at limited passages and shed light on precision cancer medicine. In this review, we summarize the methodology, advantages/disadvantages and applications of PDX models in hepatopancreatobiliary cancer research.

Personalized Treatment of Advanced Gastric Cancer Guided by the MiniPDX Model

Background

The morbidity and mortality of gastric cancer are high in China. There are challenges to develop precise and individualized drug regimens for patients with gastric cancer after a standard treatment. Choosing the most appropriate anticancer drug after a patient developing drug resistance is very important to improve the patient's prognosis. MiniPDX has been widely used as a new and reliable preclinical research model to predict the sensitivity of anticancer drugs.

Methods

The OncoVee® MiniPDX system developed by Shanghai LIDE Biotech Co., Ltd. was used to establish the MiniPDX models using specimens of patients with gastric cancer. The cancer tissues were biopsied under endoscopy, and then, the tumor cell suspension was prepared for a drug sensitivity test by subcutaneously implanting into Balb/c-nude mice. The selected optimal regimen obtained from the MiniPDX assay was used to treat patients with drug-resistant gastric cancer.

Results

We successfully established an individualized and sensitive drug screening system for four patients from January 2021 to July 2021. MiniPDX models identified potentially effective drugs for these four patients, with partial remission in two of the patients after treatment and disease progression in the remaining of two patients. Severe side effects from chemotherapy or targeted therapy were not observed in all patients.

Conclusion

Establishing a personalized drug screening system for patients with drug-resistant gastric cancer can guide the selection of clinical drugs, improve the clinical benefit of patients, and avoid ineffective treatments. It can be an effective supplement for treatment options.

The drugs screened by OncoVeeTM-Mini-PDX have significantly benefited the patient with HER2-positive advanced gastric cancer

Introduction

At present, the prognosis of HER2-positive advanced gastric cancer is extremely poor, and some patients fail to benefit from first-line Herceptin treatment, thus facing difficulties in choosing second-line drugs.

Case Report

Here, we report a 61-year-old male patient with HER2-positive advanced gastric cancer who is primarily resistant to Herceptin and has poor therapeutic effect.

Management & Outcome

Afterwards, the OncoVeeTM-MiniPDX-guided anticancer method was used to screen drugs for second-line treatment, which resulted in liquefaction and necrosis of the patient's lesions and improved liver function indicators, as well as rapid relief of the patient's clinical symptoms.

Discussion

In the treatment of the Herceptin-resistant patient with advanced gastric cancer, OncoVeeTM-MiniPDX method screened drugs and brought clinical benefits.

OncoVee™-MiniPDX-Guided Anticancer Treatment for Gastric Cancer Patients With Synchronous Liver Metastases: A Retrospective Cohort Analysis

Background

It is estimated that 35% of gastric cancer patients appear with synchronous distant metastases—the vast majority of patients presenting with metastatic hepatic disease. How to choose the most appropriate drugs or regimens is crucial to improve the prognosis of patients. We conducted this retrospective cohort analysis to evaluate the efficacy of OncoVee™-MiniPDX-guided treatment for these patients.

Methods

Gastric cancer patients with liver metastases (GCLM) were enrolled. Patients were divided into MiniPDX and control group according to their wishes. In the observation group, the OncoVee™-MiniPDX model was conducted to screen the most sensitive drug or regimens to determine the clinical administration. Meanwhile, patients were treated with regular medications in the control group according to the guidelines without the MiniPDX model. The primary endpoint was overall survival (OS), and the secondary outcomes included objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS).

Results

A total of 68 patients with GCLM were included, with the observation and control groups of 21 and 47 patients, respectively. The baseline characteristics of patients were balanced between these two groups. MiniPDX drug sensitivity tests were associated with the increased use of targeted drugs when compared with the control group (33.3 vs. 0%, p=0.032). Median OS was estimated to be 9.4 (95% CI, 7.9–11.2) months and 7.9 (95% CI, 7.2–8.7) months in the observation and control group, respectively. Both univariate (control group vs. MiniPDX group: HR=2.586, 95% CI= 1.362–4.908, p=0.004) and multivariate regression analyses (Control group vs. MiniPDX group: adjusted HR (aHR)=4.288, 95% CI= 1.452–12.671, p=0.008) showed the superiority of the observation group on OS. Similarly, MiniPDX-based regiments significantly improve the PFS of these cases (median PFS 6.7 months vs. 4.2 months, aHR=2.773, 95% CI=1.532–3.983, p=0.029). ORR and DCR were also improved in MiniPDX group comparing with control group (ORR, 57.14 vs. 25.53%, p=0.029; DCR: 85.71 vs. 68.08%, p=0.035).

Conclusion

OncoVee™-MiniPDX model, which was used to select drugs to guide antitumor treatment, was promising to prolong survival and improve the response rate of patients with GCLM. Further well-designed studies are needed to confirm the clinical benefits of MiniPDX.

Gemcitabine and XCT790, an ERRα inverse agonist, display a synergistic anticancer effect in pancreatic cancer

Pancreatic cancer (PC) is one of the most fatal and chemoresistant malignancies with a poor prognosis. The current therapeutic options for PC have not achieved satisfactory results due to drug resistance. Therefore, it is urgent to develop novel treatment strategies with enhanced efficacy. This study sought to investigate the anticancer effect of gemcitabine and XCT790, an estrogen-related receptor alpha (ERRα) inverse agonist, as monotherapies or in combination for the treatment of PC. Here we demonstrated that the drug combination synergistically suppressed PC cell viability, its proliferative, migratory, invasive, apoptotic activities, and epithelial-to-mesenchymal transition (EMT), and it triggered G0/G1 cell cycle arrest and programmed cell death in vitro. In addition, in vivo assays using xenograft and mini-PDX (patient-derived xenograft) models further confirmed the synergistic antitumor effect between gemcitabine and XCT790 on PC. Mechanistically, gemcitabine and XCT790 suppressed PC by inhibiting ERRα and MEK/ERK signaling pathway. In conclusion, our current study demonstrated for the first time that gemcitabine combined with XCT790 displayed synergistic anticancer activities against PC, suggesting that their combination might be a promising treatment strategy for the therapy of PC.

Comparative study on the efficacy and exposure of molecular target agents in non-small cell lung cancer PDX models with driver genetic alterations

Patient-derived xenografts (PDXs) can adequately reflect clinical drug efficacy. However, the methods for evaluating drug efficacy are not fully established. We selected five non-small cell lung cancer (NSCLC) PDXs with genetic alterations from established PDXs and the corresponding molecular targeted therapy was administered orally for 21 consecutive days. Genetic analysis, measurement of drug concentrations in blood and tumors using liquid chromatography and tandem mass spectrometry, and analysis of drug distribution in tumors using matrix-assisted laser desorption/ionization mass spectrometry were performed. Fifteen (20%) PDXs were established using samples collected from 76 NSCLC patients with genetic alterations. The genetic alterations observed in original patients were largely maintained in PDXs. We compared the drug efficacy in original patients and PDX models; the efficacies against certain PDXs correlated with the clinical effects, while those against the others did not. We determined blood and intratumor concentrations in the PDX model, but both concentrations were low, and no evident correlation with the drug efficacy could be observed. The intratumoral spatial distribution of the drugs was both homogeneous and heterogeneous for each drug, and the distribution was independent of the expression of the target protein. The evaluation of drug efficacy in PDXs enabled partial reproduction of the therapeutic effect in original patients. A more detailed analysis of systemic and intratumoral pharmacokinetics may help clarify the mode of action of drugs. Further development of evaluation methods and indices to improve the prediction accuracy of clinical efficacy is warranted.

Complex Tumor Spheroid Formation and One-Step Cancer-Associated Fibroblasts Purification from Hepatocellular Carcinoma Tissue Promoted by Inorganic Surface Topography

In vitro cell models play important roles as testbeds for toxicity studies, drug development, or as replacements in animal experiments. In particular, complex tumor models such as hepatocellular carcinoma (HCC) are needed to predict drug efficacy and facilitate translation into clinical practice. In this work, topographical features of amorphous silicon dioxide (SiO2) are fabricated and tested for cell culture of primary HCC cells and cell lines. The topographies vary from pyramids to octahedrons to structures named fractals, with increased hierarchy and organized in periodic arrays (square or Hexagonal). The pyramids were found to promote complex 2D/3D tissue formation from primary HCC cells. It was found that the 2D layer was mainly composed of cancer-associated fibroblasts (CAFs), while the 3D spheroids were composed of tumor cells enwrapped by a CAF layer. Compared with conventional protocols for 3D cultures, this novel approach mimics the 2D/3D complexity of the original tumor by invading CAFs and a microtumor. Topographies such as octahedrons and fractals exclude tumor cells and allow one-step isolation of CAFs even directly from tumor tissue of patients as the CAFs migrate into the structured substrate. Cell lines form spheroids within a short time. The presented inorganic topographical surfaces stimulate complex spheroid formation while avoiding additional biological scaffolds and allowing direct visualization on the substrate.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Interrogation of gender disparity uncovers androgen receptor as the transcriptional activator for oncogenic miR-125b in gastric cancer

There is a male preponderance in gastric cancer (GC), which suggests a role of androgen and androgen receptor (AR). However, the mechanism of AR signaling in GC especially in female patients remains obscure. We sought to identify the AR signaling pathway that might be related to prognosis and examine the potential clinical utility of the AR antagonist for treatment. Deep learning and gene set enrichment analysis was used to identify potential critical factors associated with gender bias in GC (n = 1390). Gene expression profile analysis was performed to screen differentially expressed genes associated with AR expression in the Tianjin discovery set (n = 90) and TCGA validation set (n = 341). Predictors of survival were identified via lasso regression analyses and validated in the expanded Tianjin cohort (n = 373). In vitro and in vivo experiments were established to determine the drug effect. The GC gender bias was attributable to sex chromosome abnormalities and AR signaling dysregulation. The candidates for AR-related gene sets were screened, and AR combined with miR-125b was associated with poor prognosis, particularly among female patients. AR was confirmed to directly regulate miR-125b expression. AR-miR-125b signaling pathway inhibited apoptosis and promoted proliferation. AR antagonist, bicalutamide, exerted anti-tumor activities and induced apoptosis both in vitro and in vivo, using GC cell lines and female patient-derived xenograft (PDX) model. We have shed light on gender differences by revealing a hormone-regulated oncogenic signaling pathway in GC. Our preclinical studies suggest that AR is a potential therapeutic target for this deadly cancer type, especially in female patients.

XPO1 inhibition synergizes with PARP1 inhibition in small cell lung cancer by targeting nuclear transport of FOXO3a

Patient mortality rates have remained stubbornly high for the past decades in small cell lung cancer (SCLC) because of having no standard targeted therapies with confirmed advantages at present. Poly [ADP-ribose] polymerase (PARP) inhibitors have shown promise in preclinical models but have had unsatisfactory clinical results in SCLC. By RNA-seq and isobaric tags for relative and absolute quantification (ITRAQ), we revealed that PARP1 inhibition led to the relocalization of forkhead box-O3a (FOXO3a) from nuclear to cytoplasm. By performing co-Immunoprecipitation (co-IP) and CRISPR-Cas9-mediated knockout plasmid we showed that FOXO3a was subject to exportin 1 (XPO1)-dependent nuclear export. We demonstrated the effects of the PARP inhibitor BMN673 on apoptosis and DNA damage were markedly enhanced by simultaneous inhibition of XPO1 in vitro. The combination of BMN673 and the XPO1 inhibitor selinexor inhibited primary SCLC cell proliferation in mini-patient-derived xenotransplants (miniPDXs) and markedly inhibited tumor growth without significant toxicity in xenograft models. The efficacy was enhanced for more than 2.5 times, compared to the single agent. Based on these findings, we further designed a novel dual PARP-XPO1 inhibitor and showed its effectiveness in SCLC. In this work, we illustrated that combining a PARP inhibitor with an XPO1 inhibitor is associated with significantly improved efficacy and tolerability. Dual PARP-XPO1 inhibition restored the FOXO3a balance and activity in SCLC. Collectively, targeting PARP1 and XPO1 opens new avenues for therapeutic intervention against SCLC, warranting further investigation in potential clinical trials.

Application of Animal Models in Cancer Research: Recent Progress and Future Prospects

Animal models refers to the animal experimental objects and related materials that can simulate human body established in medical research. As the second-largest disease in terms of morbidity and mortality after cardiovascular disease, cancer has always been the focus of human attention all over the world, which makes it a research hotspot in the medical field. At the same time, more and more animal models have been constructed and used in cancer research. With the deepening of research, the construction methods of cancer animal models are becoming more and more diverse, including chemical induction, xenotransplantation, gene programming, and so on. In recent years, patient-derived xenotransplantation (PDX) model has become a research hotspot because it can retain the microenvironment of the primary tumor and the basic characteristics of cells. Animal models can be used not only to study the biochemical and physiological processes of the occurrence and development of cancer in objects but also for the screening of cancer drugs and the exploration of gene therapy. In this paper, several main tumor animal models and the application progress of animal models in tumor research are systematically reviewed. Finally, combined with the latest progress and development trend in this field, the future research of tumor animal model was prospected.

Integrated Omics of Metastatic Colorectal Cancer

We integrate the genomics, proteomics, and phosphoproteomics of 480 clinical tissues from 146 patients in a Chinese colorectal cancer (CRC) cohort, among which 70 had metastatic CRC (mCRC). Proteomic profiling differentiates three CRC subtypes characterized by distinct clinical prognosis and molecular signatures. Proteomic and phosphoproteomic profiling of primary tumors alone successfully distinguishes cases with metastasis. Metastatic tissues exhibit high similarities with primary tumors at the genetic but not the proteomic level, and kinase network analysis reveals significant heterogeneity between primary colorectal tumors and their liver metastases. In vivo xenograft-based drug tests using 31 primary and metastatic tumors show personalized responses, which could also be predicted by kinase-substrate network analysis no matter whether tumors carry mutations in the drug-targeted genes. Our study provides a valuable resource for better understanding of mCRC and has potential for clinical application.

MiniPDX-guided postoperative anticancer treatment can effectively prolong the survival of patients with hepatocellular carcinoma

BACKGROUND

The recurrence rate of hepatocellular carcinoma (HCC) after partial hepatectomy is still high. How to choose the most appropriate anti-tumor drug in the early postoperative period is crucial to improve the prognosis of patients. Recently, MiniPDX has been widely used as a new and reliable preclinical research model capable of predicting the sensitivities of anti-tumor drugs.

METHODS

Twenty-eight patients with HCC were selected to use the MiniPDX model to screen the most sensitive anti-tumor drugs from five groups of drug regimens for preventive treatment after partial hepatectomy, and another 42 patients with HCC were selected to be treated with Sorafenib during the same period as the control group. The tumor-free survival rate and overall survival rate were analyzed and compared between these two groups. The relationship between drug sensitivity and biomarkers related to HCC was also analyzed.

RESULTS

Kaplan-Meier survival curve analysis showed that the tumor-free survival (DFS) of patients in the MiniPDX group was significantly longer than that in the control group (median DFS: 25.8 months vs. 18.2 months, P = 0.022, HR 2.19, 95% CI 1.17-4.12). The overall survival (OS) of the patients in the MiniPDX group was also longer than that in the control group (median OS: 29.4 months vs. 23.8 months, P = 0.039, HR 2.37, 95% CI 1.12-5.00). The longest follow-up period was 36 months. The relationship analyzed between the efficacy of the five drugs (Regorafenib, Regorafenib, Lenvatinib, Gemcitabine, 5-FU + Oxaliplatin) and AFP, Ki-67, VEGFR, FGFR, P53, and Nrf2 showed different correlations.

CONCLUSION

The use of the MiniPDX model to select drugs to guide anti-tumor treatment after partial hepatectomy could effectively prolong the survival of patients with HCC.