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IMPORTANCE: Although effective vaccines against COVID-19 have been developed, additional vaccines are still needed. OBJECTIVE: To evaluate the efficacy and adverse events of 2 inactivated COVID-19 vaccines. DESIGN, SETTING, AND PARTICIPANTS: Prespecified interim analysis of an ongoing randomized, double-blind, phase 3 trial in the United Arab Emirates and Bahrain among adults 18 years and older without known history of COVID-19. Study enrollment began on July 16, 2020. Data sets used for the interim analysis of efficacy and adverse events were locked on December 20, 2020, and December 31, 2020, respectively. INTERVENTIONS: Participants were randomized to receive 1 of 2 inactivated vaccines developed from SARS-CoV-2 WIV04 (5 µg/dose; n = 13 459) and HB02 (4 µg/dose; n = 13 465) strains or an aluminum hydroxide (alum)–only control (n = 13 458); they received 2 intramuscular injections 21 days apart. MAIN OUTCOMES AND MEASURES: The primary outcome was efficacy against laboratory-confirmed symptomatic COVID-19 14 days following a second vaccine dose among participants who had no virologic evidence of SARS-CoV-2 infection at randomization. The secondary outcome was efficacy against severe COVID-19. Incidence of adverse events and reactions was collected among participants who received at least 1 dose. RESULTS: Among 40 382 participants randomized to receive at least 1 dose of the 2 vaccines or alum-only control (mean age, 36.1 years; 32 261 [84.4%] men), 38 206 (94.6%) who received 2 doses, contributed at least 1 follow-up measure after day 14 following the second dose, and had negative reverse transcriptase–polymerase chain reaction test results at enrollment were included in the primary efficacy analysis. During a median (range) follow-up duration of 77 (1-121) days, symptomatic COVID-19 was identified in 26 participants in the WIV04 group (12.1 [95% CI, 8.3-17.8] per 1000 person-years), 21 in the HB02 group (9.8 [95% CI, 6.4-15.0] per 1000 person-years), and 95 in the alum-only group (44.7 [95% CI, 36.6-54.6] per 1000 person-years), resulting in a vaccine efficacy, compared with alum-only, of 72.8% (95% CI, 58.1%-82.4%) for WIV04 and 78.1% (95% CI, 64.8%-86.3%) for HB02 (P

Background We aimed to assess the safety and immunogenicity of an inactivated vaccine against COVID-19 in Chinese adults aged ≥18 years. Methods This is an ongoing randomized, double-blind, placebo-controlled, phase 1/2 clinical trial among healthy adults aged ≥18 years in Henan Province, China. Participants (n = 336 in 18–59 age group and n = 336 in ≥60 age group) were enrolled between April 12 and May 17 2020, and were equally randomized to receive vaccine or placebo (aluminum hydroxide adjuvant) in a three-dose schedule of 2·5, 5, or 10 µg on days 0, 28, and 56. Another 448 adults aged 18–59 years were equally allocated to four groups (a one-dose schedule of 10 µg, and two-dose schedules of 5 µg on days 0 and 14/21/28) and received vaccine or placebo (ratio 3:1 within each group). The primary outcomes were 7-day post-injection adverse reactions and neutralizing antibody titres on days 28 and 90 after the whole-course vaccination. Trial registration: www.chictr.org.cn #ChiCTR2000031809. Findings The 7-day adverse reactions occurred in 4·8% to 32·1% of the participants in various groups, and most adverse reactions were mild, transient, and self-limiting. Twenty participants reported 68 serious adverse events which were judged to be unrelated to the vaccine. The 90-day post-injection geometric mean titres of neutralizing antibody ranged between 87 (95% CI: 61–125) and 129 (99–169) for three-dose schedule among younger and older adults; 20 (14–27), 53 (38–75), and 44 (32–61) in 5 µg days 0 and 14/21/28 groups, respectively, and 7 (6–9) in one-dose 10 µg group. There were no detectable antibody responses in all placebo groups. Interpretation The inactivated vaccine against COVID-19 was well tolerated and immunogenic in both younger and older adults. The two-dose schedule of 5 µg on days 0 and 21/28 and three-dose schedules on days 0, 28, and 56 could be further evaluated for long-term safety and efficacy in the phase 3 trials. Funding The study was funded by the National Program on Key Research Project of China (2020YFC0842100) and Major Science and Technology Project of the National New Drug Development of China (2018ZX09734-004).

Summary Background The ongoing COVID-19 pandemic warrants accelerated efforts to test vaccine candidates. We aimed to assess the safety and immunogenicity of an inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine candidate, BBIBP-CorV, in humans. Methods We did a randomised, double-blind, placebo-controlled, phase 1/2 trial at Shangqiu City Liangyuan District Center for Disease Control and Prevention in Henan Province, China. In phase 1, healthy people aged 18–80 years, who were negative for serum-specific IgM/IgG antibodies against SARS-CoV-2 at the time of screening, were separated into two age groups (18–59 years and ≥60 years) and randomly assigned to receive vaccine or placebo in a two-dose schedule of 2 μg, 4 μg, or 8 μg on days 0 and 28. In phase 2, healthy adults (aged 18–59 years) were randomly assigned (1:1:1:1) to receive vaccine or placebo on a single-dose schedule of 8 μg on day 0 or on a two-dose schedule of 4 μg on days 0 and 14, 0 and 21, or 0 and 28. Participants within each cohort were randomly assigned by stratified block randomisation (block size eight) and allocated (3:1) to receive vaccine or placebo. Group allocation was concealed from participants, investigators, and outcome assessors. The primary outcomes were safety and tolerability. The secondary outcome was immunogenicity, assessed as the neutralising antibody responses against infectious SARS-CoV-2. This study is registered with www.chictr.org.cn, ChiCTR2000032459. Findings In phase 1, 192 participants were enrolled (mean age 53·7 years [SD 15·6]) and were randomly assigned to receive vaccine (2 μg [n=24], 4 μg [n=24], or 8 μg [n=24] for both age groups [18–59 years and ≥60 years]) or placebo (n=24). At least one adverse reaction was reported within the first 7 days of inoculation in 42 (29%) of 144 vaccine recipients. The most common systematic adverse reaction was fever (18–59 years, one [4%] in the 2 μg group, one [4%] in the 4 μg group, and two [8%] in the 8 μg group; ≥60 years, one [4%] in the 8 μg group). All adverse reactions were mild or moderate in severity. No serious adverse event was reported within 28 days post vaccination. Neutralising antibody geometric mean titres were higher at day 42 in the group aged 18–59 years (87·7 [95% CI 64·9–118·6], 2 μg group; 211·2 [158·9–280·6], 4 μg group; and 228·7 [186·1–281·1], 8 μg group) and the group aged 60 years and older (80·7 [65·4–99·6], 2 μg group; 131·5 [108·2–159·7], 4 μg group; and 170·87 [133·0–219·5], 8 μg group) compared with the placebo group (2·0 [2·0–2·0]). In phase 2, 448 participants were enrolled (mean age 41·7 years [SD 9·9]) and were randomly assigned to receive the vaccine (8 μg on day 0 [n=84] or 4 μg on days 0 and 14 [n=84], days 0 and 21 [n=84], or days 0 and 28 [n=84]) or placebo on the same schedules (n=112). At least one adverse reaction within the first 7 days was reported in 76 (23%) of 336 vaccine recipients (33 [39%], 8 μg day 0; 18 [21%], 4 μg days 0 and 14; 15 [18%], 4 μg days 0 and 21; and ten [12%], 4 μg days 0 and 28). One placebo recipient in the 4 μg days 0 and 21 group reported grade 3 fever, but was self-limited and recovered. All other adverse reactions were mild or moderate in severity. The most common systematic adverse reaction was fever (one [1%], 8 μg day 0; one [1%], 4 μg days 0 and 14; three [4%], 4 μg days 0 and 21; two [2%], 4 μg days 0 and 28). The vaccine-elicited neutralising antibody titres on day 28 were significantly greater in the 4 μg days 0 and 14 (169·5, 95% CI 132·2–217·1), days 0 and 21 (282·7, 221·2–361·4), and days 0 and 28 (218·0, 181·8–261·3) schedules than the 8 μg day 0 schedule (14·7, 11·6–18·8; all p Interpretation The inactivated SARS-CoV-2 vaccine, BBIBP-CorV, is safe and well tolerated at all tested doses in two age groups. Humoral responses against SARS-CoV-2 were induced in all vaccine recipients on day 42. Two-dose immunisation with 4 μg vaccine on days 0 and 21 or days 0 and 28 achieved higher neutralising antibody titres than the single 8 μg dose or 4 μg dose on days 0 and 14. Funding National Program on Key Research Project of China, National Mega projects of China for Major Infectious Diseases, National Mega Projects of China for New Drug Creation, and Beijing Science and Technology Plan.

Additional file 3: Figure S2. Volcano plot of T1/T3 vs. T7/T9, T1/T3 vs. T7/9 and T1/T3 vs. T10/12 of upgenes and downgenes.

Additional file 2: Figure S1. Differential expression of KEGG pathway-related genes.

Additional file 4: Figure S3. The figure is unigenes contrasted to the COG database.

Importance A vaccine against coronavirus disease 2019 (COVID-19) is urgently needed. Objective To evaluate the safety and immunogenicity of an investigational inactivated whole-virus COVID-19 vaccine in China. Interventions In the phase 1 trial, 96 participants were assigned to 1 of the 3 dose groups (2.5, 5, and 10 μg/dose) and an aluminum hydroxide (alum) adjuvant-only group (n = 24 in each group), and received 3 intramuscular injections at days 0, 28, and 56. In the phase 2 trial, 224 adults were randomized to 5 μg/dose in 2 schedule groups (injections on days 0 and 14 [n = 84] vs alum only [n = 28], and days 0 and 21 [n = 84] vs alum only [n = 28]). Design, setting, and participants Interim analysis of ongoing randomized, double-blind, placebo-controlled, phase 1 and 2 clinical trials to assess an inactivated COVID-19 vaccine. The trials were conducted in Henan Province, China, among 96 (phase 1) and 224 (phase 2) healthy adults aged between 18 and 59 years. Study enrollment began on April 12, 2020. The interim analysis was conducted on June 16, 2020, and updated on July 27, 2020. Main outcomes and measures The primary safety outcome was the combined adverse reactions 7 days after each injection, and the primary immunogenicity outcome was neutralizing antibody response 14 days after the whole-course vaccination, which was measured by a 50% plaque reduction neutralization test against live severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Results Among 320 patients who were randomized (mean age, 42.8 years; 200 women [62.5%]), all completed the trial up to 28 days after the whole-course vaccination. The 7-day adverse reactions occurred in 3 (12.5%), 5 (20.8%), 4 (16.7%), and 6 (25.0%) patients in the alum only, low-dose, medium-dose, and high-dose groups, respectively, in the phase 1 trial; and in 5 (6.0%) and 4 (14.3%) patients who received injections on days 0 and 14 for vaccine and alum only, and 16 (19.0%) and 5 (17.9%) patients who received injections on days 0 and 21 for vaccine and alum only, respectively, in the phase 2 trial. The most common adverse reaction was injection site pain, followed by fever, which were mild and self-limiting; no serious adverse reactions were noted. The geometric mean titers of neutralizing antibodies in the low-, medium-, and high-dose groups at day 14 after 3 injections were 316 (95% CI, 218-457), 206 (95% CI, 123-343), and 297 (95% CI, 208-424), respectively, in the phase 1 trial, and were 121 (95% CI, 95-154) and 247 (95% CI, 176-345) at day 14 after 2 injections in participants receiving vaccine on days 0 and 14 and on days 0 and 21, respectively, in the phase 2 trial. There were no detectable antibody responses in all alum-only groups. Conclusions and relevance In this interim report of the phase 1 and phase 2 trials of an inactivated COVID-19 vaccine, patients had a low rate of adverse reactions and demonstrated immunogenicity; the study is ongoing. Efficacy and longer-term adverse event assessment will require phase 3 trials. Trial registration Chinese Clinical Trial Registry Identifier: ChiCTR2000031809.

Fruit spine size is one of the importantly external quality traits effected the economic value of cucumber fruit. Morphological–cytological observation of the fruit spine size phenotype indicated that large spine formation arises from an increasing of spiny pedestal cell number caused by cell division, and best periods to accurately score fruit spine size trait was 4th day before flowering to 7th day after flowering according the continuous observation. Genetic analysis showed that a single dominant gene determined the fruit spine size trait in cucumber. BC1 population (189 individuals) of two inbred lines (large spine PI197088 and small spine SA0422) was used for primary mapping of the SS/ss locus with 7 markers covering an interval of 37.1 cM. An F2 segregating population of 1032 individuals constructed from the same two parents (PI197088 and SA0422) was used to fine mapping of the SS/ss locus. Six new markers linked to the gene were successfully screened for construction of a fine linkage map, in which the SS/ss locus was located in the region flanked by marker SE1 (3 recombinants) and SSR43 (2 recombinants) with a 189 kb physical distance. Markers from this study will be valuable for candidate gene cloning and marker-assisted selection for cucumber breeding.

Cucumber fruits that have tubercules and spines (trichomes) are known to possess a warty (Wty) phenotype. In this study, the tuberculate fruit gene Tu was identified by map-based cloning, and was found to encode a transcription factor (TF) with a single C2 H2 zinc finger domain. Tu was identified in all 38 Wty lines examined, and was completely absent from all 56 non-warty (nWty) lines. Cucumber plants transgenic for Tu (TCP) revealed that Tu was required for the Wty fruit phenotype. Subcellular localization showed that the fusion protein GFP-Tu was localized mainly to the nucleus. Based on analyses of semi-quantitative and quantitative reverse transcription polymerase chain reaction (RT-PCR), and mRNA in situ hybridization, we found that Tu was expressed specifically in fruit spine cells during development of fruit tubercules. Moreover, cytokinin (CTK) content measurements and cytological observations in Wty and nWty fruits revealed that the Wty fruit phenotype correlated with high endogenous CTK concentrations. As a result of further analyses on the transcriptomic profile of the nWty fruit epidermis and TCP fruit warts, expression of CTK-associated genes, and hormone content in nWty fruit epidermis, Wty fruit warts and epidermis, and TCP fruit warts and epidermis, we found that Tu probably promoted CTK biosynthesis in fruit warts. Here we show that Tu could not be expressed in the glabrous and tubercule-free mutant line gl that contained Tu, this result that futher confirmed the epistatic effect of the trichome (spine) gene Gl over Tu. Taken together, these data led us to propose a genetic pathway for the Wty fruit trait that could guide future mechanistic studies.

Mottled/uniform color at the flower end of immature fruit is a highly important external quality trait that affects the market value of cucumber. Genetic analysis of different F2 and backcross populations revealed that one single recessive gene, u (uniform immature fruit color), determines the uniform immature fruit color trait in cucumber. Based on earlier studies, the u locus is located on chromosome 5 (Chr. 5). By combining bulked segregant analysis using 60 published molecular markers on Chr. 5, we found that eight markers are polymorphic and are linked to the u locus. In addition, we developed five new relevant polymorphic simple sequence repeat (SSR) markers between markers SSR16203 and SSR15818. Subsequently, the F2 population (477 individuals) from the cross of S06 (uniform fruit color line) × S94 (mottled fruit color line) was used for fine mapping of the u gene. The u gene was mapped to a 313.2-kb region between markers SSR10 and SSR27, at a genetic distance of 0.8 and 0.5 cM, respectively. Moreover, validity analysis of the codominant markers SSR10 and SSR27 was performed using 50 lines with mottled/uniform fruit color, demonstrating that these two SSR markers can be used for marker-assisted selection of the mottled/uniform fruit color trait in cucumber breeding. The results of this study will facilitate the cloning of the u gene.

Precision oncology requires identifying and understanding of cancer genome changes in a patient tumor tissue and finding the best cancer therapy targeting the changes. Although many cancer gene targets have been validated so far, next-generation genomic profile analyses have uncovered much more cancer gene variants with unconfirmed functions. Developing methods to functionally evaluate mutations/variants and understand their roles in cancer development and drug responses, such as drug resistance or synthetic lethality, will be critical in cancer treatment decision support. In addition, in some clinical cases, multiple treatment choices such as multiple drug combinations exist. Developing cancer models which can test multiple treatments will provide direct comparison of those therapies and select the best options. At GenenDesign, we have performed drug tests on mouse “avatars”, which are also known as Patient-Derived Xenograft (PDX) models. They are personalized cancer models derived from patient tumor samples with cancer mutation profiles and drug responses very similar to the corresponding cancer patients. Drug screenings were carried out in avatars by testing chemotherapies or targeted drugs against specific cancer gene mutations and variants. Selected drugs or drug combinations from avatar studies have been applied to corresponding patients with highly consistent treatment outcome. From genomic profile analysis of our near 1500 PDX tumor models in cancer types such as lung, colorectal, gastric, liver, and esophageal, we are able to identify a large number of cancer gene mutations/variants, gene fusions, as well as gene copy number and RNA expression changes in major cancer signal pathways such as EGFR, Her2, c-Met/ALK, Ras/Raf, FGFRs, PI3K/Akt, Wnt, Notch, DNA repair, cell cycle regulation, angiogenesis. Many of these gene aberrations are potential drug targets and have been functionally tested in PDX models with approved drugs or clinical drug candidates. The mutation/variant information and drug response information generated from PDX models have been organized into our Precision Cancer Information Lab database. Patient tumor DNA test results have been used for searching genetically matched PDX models in our database. Once matched PDX models are identified, the available drug response information can be used as evidence for clinical treatment decision. In addition, the matched PDX models can also been used to test more treatment options such as different combinations and new clinical drug candidates. Citation Format: Jingjing Jiang, Tengfei Yu, Ying Yan, Wei Du, Tingting Tan, Xuqin Yang, Jiali Gu, Ling Qiu, Xin K. Ye, Zhenyu Gu. In vivo functional analyses of cancer gene variants for cancer driver identification and drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3139. doi:10.1158/1538-7445.AM2017-3139

Cancer is a heterogeneous disease with various molecular lesions and drug response profiles within the same tumor type. Patient stratification in clinical trials based on molecular features has contributed to recent success of several targeted cancer drugs on molecular aberrations such as BCR-ABL translocation in CML, Her2 amplification in breast and gastric cancers, EGFR mutations and ALK fusions in lung cancer and BRAF mutation in melanoma. However, in most cancers, the molecular features which can be used for patient stratification are not as simple as a single genetic aberration. Multiple drug resistance mechanisms caused by various mutations in cancer signaling pathways can also increase the uncertainty of clinical outcomes. To increase the chance of success in human clinical studies, patient-derived xenograft (PDX) clinical trials (PCTs) have increasingly been used for predictive biomarker validation, resistance mechanism investigation and combination therapy selection. PDX tumor models have been demonstrated to have high correlations with human patients in tumor pathology, molecular characteristics and drug responses. Large scale PCTs have also shown consistency in results when compared to related human clinical trials. At GenenDesign, we have established over 1000 PDX tumor models and more than 100 resistance models against various cancer drugs. Many of these PDX models have been characterized at RNA/Exome sequence, gene expression, gene copy number and hot-spot mutation levels. We carried out our PDX clinical trials by testing multiple approved drugs and clinical drug candidates such as targeted inhibitors against FGFRs, c-Met/ALK, HER2, EGFR, cell cycle regulators, Ras/Raf pathway, PI3K/Akt pathway, as well as chemotherapy drugs in biomarker-driven multi-drug multi-arm expanded PDX clinical trials. So far, we have accumulated more than 3000 efficacy data sets and associated PD samples. Analysis of drug response and associated genomic information from PDX clinical trials yielded rich information for predictive biomarker identification and validation. At the same time, many potential resistance mechanisms were also revealed. These information can make human clinical trial better prepared, more efficient and focused. More importantly, testing of a targeted drug with multiple chemotherapies in the same models can also provide guidance on future combination selection strategy. Citation Format: Jingjing Jiang, Tengfei Yu, Ying Yan, Wei Du, Tingting Tan, Xuqin Yang, Jiali Gu, Xin K. Ye, Zhenyu Gu. Patient stratification and drug combination strategy based on drug response and genomic information from PDX clinical trials (PCTs). [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 395.

The main purpose of precision medicine is to find the right drug for the right patient at the right time. Current progress in cancer drug target identification and development of new targeted drugs has presented many successful examples. However, for majority of patients, finding treatments based on the unique mutations in their own tumor cells are still hard. New approaches for precision medicine are in great needs and thus being investigated. A mouse “avatar”, also known as Patient-Derived Xenograft (PDX) model, is a personalized cancer model derived from a patient tumor sample and used to test different drugs for the patient. “GIFTS” (or Genomic Information Fitting based Therapeutics Selection) is a method with which a patient's cancer genomic information is compared to PDX model genomic profiles to find the best genomic fit and related therapeutic options in GenenDesign Drug Response Database and Genomic Information database. So far we have successfully derived more than 1000 PDX models from patient tumor tissues of various cancer types including lung, gastric, liver, esophageal, colorectal, pancreatic and many other cancers. In some cases, both patients and their avatars were tested with same cancer drugs including targeted drugs and chemotherapies. By comparing drug responses in mouse avatars with patient clinical results, we found high correlations between them in both sensitivity and unresponsiveness. We have also developed a bioinformatics algorithm to analyze PDX model genomic and drug response information. Both drug sensitivity and resistance biomarkers have been used in matching cancer patient genomic profiles to those of PDX models in GenenDesign database as a part of our GIFTS method. Our preliminary results show that there are high degree of similarities in drug response profiles between patients and their matched PDX models. Avatar and GIFTS methods can provide predictions of therapeutic effectiveness on both targeted drugs and chemotherapies. Avatar is a drug screening based method, while GIFTS is a genomic profile matching based method. Both methods are especially useful for patients, whose tumors could not be treated with known targeted drugs. Citation Format: Jingjing Jiang, Ying Yan, Zhongguang Luo, Jia He, Tengfei Yu, Wei Du, Xuqin Yang, Jiali Gu, Xin K. Ye, Guanglei Zhuang, Jie Liu, Zhenyu Gu. Prediction and selection of cancer drug treatments using personalized tumor models or models with matching genomic profiles. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3982.

Companion diagnostics are assays intended to find the right drug for the right patient in targeted cancer therapy. Biomarker discovery is the first step in companion diagnostics development. Currently great efforts have been devoted to biomarker discovery and validation through analysis of clinical samples. However, the quantity and quality of tumor samples from drug candidate treated patients are very limited during drug development, which has posed challenges for fast and cost-effective drug-diagnostic co-development. Patient derived xenograft (PDX) tumor models have been demonstrated to represent cancer complexity and heterogeneity known in patients. Drug targets and responses to targeted drugs in PDX models show high correlation to those in cancer patients. We have established over 950 PDX tumor models and around 100 resistance models to drugs of interest. To evaluate mouse trials with PDX models as biomarker discovery platform, we have been testing PDX models with SOCs and clinical drug candidates such as targeted inhibitors against FGFRs, c-Met/ALK, HER2, EGFR, cell cycle regulators, Ras/Raf pathway, PI3K/Akt pathway, as well as chemotherapy drugs in a biomarker-driven multi-drug multi-arm clinical trial setting, and have accumulated more than 1500 data sets and associated PD samples. Through analysis of drug response data and genomic profile data from PDX models, we show that many of the drug sensitivity biomarkers and drug resistance biomarkers identified in clinical studies can be faithfully found in PDX studies. Moreover, some novel predictive biomarkers for candidate drugs in relatively early clinical stage have also been identified and will be further validated in future clinical studies. The availability of a large number of PDX models, the flexibility of designing studies and the quickness in testing new drug candidates make this type of mouse trial and its derived data sets a useful platform for biomarker discovery in companion diagnostics development. Citation Format: Jingjing Jiang, Tengfei Yu, Ying Yan, Wei Du, Tingting Tang, Xuqin Yang, Jiali Gu, Liang Hua, Xin Katherine Ye, Zhenyu Gu. Accelerating biomarker discovery for companion diagnostics through mouse trials with PDX models in clinical settings. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A32.

Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocelluar carcinoma (HCC) is the most common form of liver cancer, followed by intrahepatic cholangiocarcinoma (IHCC). HCC has dismal clinical outcome, whereas the prognosis is even worse for IHCC as it is more difficult to diagnose and to treat comparing to HCC. Surgical resection and local ablation remain the top choices of therapy for early liver cancer while chemoembolization-TACE is commonly used to treat intermediate HCC. Sorafenib is the only FDA approved target therapy for advanced HCC and its clinical utility in IHCC is still being examined in clinical trials. On-going clinical trials are also testing therapeutic modalities against oncogenic pathways including RTK signaling pathways, PI3K/Ras pathways and the angiogenesis pathway. PDX tumor models recapitulate the clinical complexity of the original human cancers. At GenenDesign, we have established over 800 PDX tumor models and conducted extensive drug response tests in a mouse trial format. GenenDesign liver cancer PDX tumor panel comprises of 36 HCC and over 10 IHCC models. Our in-house mouse trials in liver PDX tumor models include treatment with sorafenib as well as XL184, a multi-kinase inhibitor currently being evaluated in clinical trials. In addition, crizotinib (a cMET inhibitor) and AZD4547 (an FGFR inhibitor) as mono-therapies as well as in combination with sorafenib are also tested in search of therapeutic signals. From these studies, we have identified both drug sensitive and de novo drug resistant models. Through long-term treatment, acquired resistance models and reversible resistance models are also established. Currently, GD liver cancer PDX tumors are being analyzed by genetic and genomic profiling (hot-spot mutational analysis, exome-seq, RNA-seq, SNP array and gene expression array). Bioinformatics analysis is on-going to identify genomic signatures with the potential as predictive biomarkers for sorafenib and other targeted therapies in liver cancer. Together with genomic profiling, signal search in PDX mouse trials promise to be effective in generating preclinical datasets to facilitate clinical trial designs. Citation Format: Tengfei Yu, Ying Yan, Wei Du, Liang Hua, Xuqin Yang, Tingting Tan, Jiali Gu, Jingjing Jiang, Xin K. Ye, Zhenyu Gu. Effect of target therapies in liver cancer PDX tumor models: Response, resistance and predictive biomarkers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1476. doi:10.1158/1538-7445.AM2015-1476

Patient derived xenograft (PDX) tumor models have been proved to recapitulate the complexity and heterogeneity of their corresponding human tumors by phenotypic and genomic characterization, and thus become to be widely used in recent years in preclinical setting to facilitate drug discovery, translational studies and clinical trials support. Results from increasing number of preclinical studies, especially mouse trials, with PDX models in the past several years, have also demonstrated close correlation between drug response profiles with PDX models and clinical outcomes. GenenDesign has established over 800 PDX tumor models and derived around 100 resistance models to drugs of interest. Genomic profiling data of PDX models are acquired at hot-spot mutation, gene expression, gene copy number and RNA/Exome sequence levels. Through our in-house efforts, PDX models of different tumor types were tested with related SOCs and clinical candidates in biomarker-driven multi-drug multi-arm clinical trial settings. So far, more than 1200 data sets have been generated, including responses to targeted inhibitors against HER2, EGFR, FGFRs, c-Met/ALK, cell cycle regulators, Ras/Raf pathway, PI3K/Akt pathway, epigenetic targets, as well as chemotherapy drugs. In this study, we use bioinformatic tools to compare the genomic profiles of NSCLC PDX models based on their response profiles to multiple chemotherapy drugs. Biomarker signatures associated with SOC treatment sensitivity or resistance are revealed from bioinformatic analysis and being tested with both new NSCLC PDX models and clinical cohorts. The combination of genomic profiles and drug response information to multiple chemo/targeted therapies of over 800 PDX models at GenenDesign would help biomarker discovery for companion diagnosis to meet the increasing needs for precision medicine. Citation Format: Jingjing Jiang, Tengfei Yu, Ying Yan, Wei Du, Tingting Tan, Xuqin Yang, Jiali Gu, Liang Hua, Katherine Xin Ye, Zhenyu Gu. Biomarker discovery through bioinformatic analysis of genomic profiles of PDX models with different responses to cancer therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3222. doi:10.1158/1538-7445.AM2015-3222

From Chinese cancer patients, close to 600 patient derived xenograft (PDX) tumor models have been established (> P3, three passages in mice) at GenenDesign through serial passages in the immune-compromised nude mice. The major collection of GenenDesign PDX tumor model platform represents cancer types that are prevalent in Asian patients, including gastric cancer (> 200 models), esophageal cancer (>100 models), liver cancer (∼50 models), pancreatic cancer (>60 models) and lung cancer (> 80 models). Establishment of variant PDX models from the same patient tumor is on-going to support translational studies of tumor heterogeneity. Initial characterization indicates that the mouse PDX models have captured the major histopathological characteristics of the original human tumors. Reproducible growth curves for PDX models (>P3) support their usage in efficacy analysis of anti-cancer therapeutic agents. Response curves to SoC (standard of care) chemotherapies such as Paclitaxel for lung cancer, FOLFOX for gastric cancer and Sorafenib for liver cancer have been established in the PDX tumor models, providing a baseline for further investigation of novel therapies in a combination setting. On-going molecular characterization including oncogene mutational analysis and target specific IHC and FISH analysis has identified panels of PDX tumor models with aberrations in key oncogenic signaling pathways, including lung panels with EGFR overexpression or KRAS mutations, gastric panels with FGFR2 amplification or being HER2 positive, lung and gastric panels with cMET overexpression. Testing of Herceptin in the gastric HER2 positive tumor panel resulted in observations similar to that from the ToGA trial. At the same time, Herceptin resistant PDX tumor variants (de novo or acquired) were identified or established. The PDX tumor model panels facilitate translational studies in a “mouse trial” format in a setting similar to clinical trials to test patient stratification strategies and drug response predictive biomarkers for emerging therapeutic modalities. Citation Format: Ying Yan, Tengfei Yu, Wei Du, Guosheng Tong, Yuefei Yang, Tingting Tan, Xuqin Yang, Zhenhua Liu, Jiali Gu, Liang Hua, Wei Zhang, Xin K. Ye, Zhenyu Gu. A patient derived xenograft tumor model platform for “mouse trials”. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1210. doi:10.1158/1538-7445.AM2014-1210

Anti-cancer drugs, either targeted therapies or cytotoxic chemotherapies, have proven to be effective in treating certain cancer patients. However, in most cases, tumors recur and become resistant to the treatment after a period of time. There are urgent needs to understand the underlying drug resistance mechanisms, to discover drug resistance targets and drug resistance biomarkers and to develop new therapies or combination therapies to tackle this widely occurring clinical problem. Currently the main approaches to study cancer drug resistance include analyzing clinical samples and developing drug resistance models in vitro. Numerous potential resistance mechanisms have been revealed. However, validation of these findings in a clinical-like setting and to test therapies in preclinical studies requires in vivo tumor models of drug resistance. At GenenDesign, we have developed cancer drug resistance PDX tumor models through short term drug testing or long term treatment of xenograft tumor mice. Cancer drugs investigated in our studies include major classes of targeted therapeutic modalities such as Her2 inhibitors, EGFR inhibitors, FGFR inhibitors and cMet/ALK inhibitors, as well as several standard of care (SoC) chemotherapies. From these studies, we have identified de novo resistance models, acquired resistance models and reversible resistance models in multiple cancer types including lung cancer and gastric cancer. In analyzing more than a dozen of Her2 positive but Herceptin resistance PDX models, we have uncovered molecular abnormalities such as Pten deletion, PI3K mutation, amplification of EGFR, cMet and cyclin E, which have been reported previously to be associated with Herceptin resistance in early studies. Studies are on-going to test whether combination therapies will be effective in overcoming Herceptin resistance. In drug response profiling of our PDX models, we also found wide spread phenotypical and functional heterogeneity in individual tumors. The heterogeneity within each tumor, in some cases, contributed to evolving of drug resistance from initially responsive tumors. Citation Format: Tengfei Yu, Ying Yan, Wei Du, Yuefei Yang, Tingting Tan, Xuqin Yang, Jiali Gu, Liang Hua, Xin K. Ye, Zhenyu Gu. Studying cancer drug resistance in patient derived xenograft tumor models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1212. doi:10.1158/1538-7445.AM2014-1212