Phase II study of ceralasertib (AZD6738) in combination with durvalumab in patients with advanced gastric cancer.

BACKGROUND: Targeting the DNA damage repair (DDR) pathways is an attractive strategy for boosting cancer immunotherapy. Ceralasertib (AZD6738) is an oral kinase inhibitor of ataxia telangiectasia and Rad3 related protein, which is a master regulator of DDR. We conducted a phase II trial of ceralasertib plus durvalumab in patients with previously treated advanced gastric cancer (AGC) to demonstrate the safety, tolerability, and clinical activity of the combination. METHODS: This phase II, open-label, single-center, non-randomized study was designed to evaluate the efficacy and safety of ceralasertib in combination with durvalumab in patients with AGC. The study drug regimen was ceralasertib (240 mg two times a day) days 15-28 in a 28-day cycle in combination with durvalumab (1500 mg) at day 1 every 4 weeks. The primary end point was overall response rate (ORR) by Response Evaluation Criteria in Solid Tumors (V.1.1). Exploratory biomarker analysis was performed using fresh tumor biopsies in all enrolled patients. RESULTS: Among 31 patients, the ORR, disease control rate, median progression-free survival (PFS), and overall survival were 22.6% (95% CI 9.6% to 41.1%), 58.1% (95% CI 39.1% to 75.5%), 3.0 (95% CI 2.1 to 3.9) months, and 6.7 (95% CI 3.8 to 9.6) months, respectively. Common adverse events were manageable with dose modification. A subgroup of patients with a loss of ataxia telangiectasia mutated (ATM) expression and/or high proportion of mutational signature attributable to homologous repair deficiency (sig. HRD) demonstrated a significantly longer PFS than those with intact ATM and low sig. HRD (5.60 vs 1.65 months; HR 0.13, 95% CI 0.045 to 0.39; long-rank p<0.001). During the study treatment, upregulation of the innate immune response by cytosolic DNA, activation of intratumoral lymphocytes, and expansion of circulating tumor-reactive CD8 +T cell clones were identified in responders. Enrichment of the tumor vasculature signature was associated with treatment resistance. CONCLUSIONS: Ceralasertib plus durvalumab has promising antitumor activity, with durable responses in patients with refractory AGC. Thus, a biomarker-driven trial is required. TRIAL REGISTRATION: NCT03780608.

Comparison of the Radiologic, Morphometric, and Clinical Outcomes between Kinematically and Mechanically Aligned Total Knee Arthroplasty: A Propensity Matching Study.

The purpose of this study was to compare radiologic, morphometric, and clinical outcomes between kinematically aligned (KA) and mechanically aligned (MA) total knee arthroplasty (TKA) in Korean patients. Overall, 168 patients who underwent primary TKA were retrospectively reviewed, and propensity matching (age, sex, and body mass index) was performed as 1:3 ration (KA TKAs [n = 42]: MA TKAs [n = 126]). Joint-line orientation angle (JLOA), coronal and axial alignments of implants, hip-knee-ankle (HKA) angle, and patellar tilt angle were assessed using full-length standing radiograph, axial computed tomography (CT) scan, and plain radiographs. Morphometric assessment was performed by analyzing the intraoperative measurement of the femoral cut surface and femoral components fitting in five zones. Clinical outcomes more than 2 years of follow-up were evaluated with the Knee Society (KS) knee and functional scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, and the Short-Form Health Survey (SF-36). In radiologic results, JLOA was more parallel to the floor in KA TKAs (KA: medial tilt 0.9 ± 1.5 degrees; MA: lateral tilt 1.7 ± 1.5 degrees, p < 0.05), and patellar tilt angle was closer to preoperative status after KA TKA (KA: 2.0 ± 1.6 degrees; MA;0.3 ± 1.2 degrees, p < 0.05). HKA angle and rotational mismatch were similar between two groups. In morphometric analysis, entire overhang of anterior femoral cutting surface was reduced in KA TKA compared with MA TKA (KA: 11.7 ± 6.2 mm; MA: 14.4 ± 5.9 mm, p < 0.05). However, both of MA and KA TKAs showed underhang in mediolateral dimension without difference. There were no significant differences in clinical scores between two groups. KA TKA showed more parallel JLOA to floor, closer patellar tilt to preoperative status, and better anterior flange fitting that can reproduce more natural knee kinematics compared with MA TKA. Although clinical outcomes assessed by conventional evaluating tools were similar between two groups, further evaluation focusing on the patellofemoral symptoms or unawareness of TKA is necessary to clarify the clinical benefit of KA TKA.

Blood Loss and Related Laboratory Changes after Single-Event Multilevel Surgery and Hip Reconstructive Surgery in Patients with Cerebral Palsy.

BACKGROUD: Single-event multilevel surgery (SEMLS) and hip reconstructive surgery (HRS) often cause intraoperative bleeding, consequently increasing the probability of transfusion and postoperative laboratory changes. Therefore, it is important to assess risk factors to predict the amount of blood loss. This study aimed to evaluate blood loss, its influencing factors, and the related laboratory changes during SEMLS and HRS in patients with cerebral palsy (CP). METHODS: We retrospectively examined consecutive CP patients who underwent SEMLS and HRS. Surrogate markers of blood loss, including preoperative and postoperative hemoglobin (Hb), hematocrit, and changes in Hb concentration, were assessed. Albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and creatine levels were also analyzed for related laboratory changes. Risk factors were analyzed using multiple regression and logistic regression models. RESULTS: The overall cohort comprised 1,188 patients. Of them, 1,007 and 181 underwent SEMLS and HRS, respectively. Furthermore, 72 of 181 patients underwent a concomitant Dega osteotomy. The regression model showed that low preoperative Hb concentration (p < 0.001), high albumin level (p = 0.007), low body mass index (BMI) (p = 0.002), and bilateral HRS (p < 0.001) were significant risk factors of postoperative anemia. Valproate medication was associated with Hb drop, and the risk factors for Hb level < 8 g/dL on postoperative day 2 were bilateral HRS and Dega osteotomy in the HRS subgroup. In total, 21.6% had elevated AST levels on postoperative day 2, and bilateral HRS (p < 0.001), Gross Motor Function Classification System (GMFCS) level V (p = 0.041), Dega osteotomy (p < 0.001), and high preoperative AST level (p < 0.001) increased the risk of AST elevation. CONCLUSIONS: We have summarized the estimated blood loss and related laboratory changes after SEMLS and HRS in patients with CP and identified the risk factors. Clinical guidelines should be accordingly developed to include assessment of these risk factors and their impact in the outcomes of CP patients undergoing SEMLS and HRS.

Determinants of Response and Intrinsic Resistance to PD-1 Blockade in Microsatellite Instability-High Gastric Cancer.

Sequence alterations in microsatellites and an elevated mutational burden are observed in 20% of gastric cancers and associated with clinical response to anti-PD-1 antibodies. However, 50% of microsatellite instability-high (MSI-H) cancers are intrinsically resistant to PD-1 therapies. We conducted a phase II trial of pembrolizumab in patients with advanced MSI-H gastric cancer and included serial and multi-region tissue samples in addition to serial peripheral blood analyses. The number of whole-exome sequencing (WES)-derived nonsynonymous mutations correlated with antitumor activity and prolonged progression-free survival (PFS). Coupling WES to single-cell RNA sequencing, we identified dynamic tumor evolution with greater on-treatment collapse of mutational architecture in responders. Diverse T-cell receptor repertoire was associated with longer PFS to pembrolizumab. In addition, an increase in PD-1+ CD8+ T cells correlated with durable clinical benefit. Our findings highlight the genomic, immunologic, and clinical outcome heterogeneity within MSI-H gastric cancer and may inform development of strategies to enhance responsiveness. SIGNIFICANCE: This study highlights response heterogeneity within MSI-H gastric cancer treated with pembrolizumab monotherapy and underscores the potential for extended baseline and early on-treatment biomarker analyses to identify responders. The observed markers of intrinsic resistance have implications for patient stratification to inform novel combinations among patients with intrinsically resistant features.See related commentary by Fontana and Smyth, p. 2126.This article is highlighted in the In This Issue feature, p. 2113.

Bispecific Antibody Molecule Inhibits Tumor Cell Proliferation More Efficiently Than the Two-Molecule Combination.

BACKGROUND: Monoclonal antibodies (mAbs) have proved to be a valuable tool for the treatment of different cancer types. However, clinical use of an increasing number of mAbs, have also highlighted limitations with monotherapy for cancers, in particular for such with more complex mechanisms, requiring action on additional molecules or pathways, or for cancers quickly acquiring resistance following monotherapy. An example for the latter is the mAb trastuzumab, FDA approved for treatment of metastatic gastric carcinoma. To circumvent this, researchers have reported synergistic, anti-proliferative effects by combination targeting of HER2 and EGFR by trastuzumab and the EGFR-targeting mAb Cetuximab overcoming trastuzumab resistance. METHODS: Maintaining the proven functionality of trastuzumab, we have designed bi-specific antibody molecules, called AffiMabs, by fusing an EGFR-targeting Affibody molecule to trastuzumab's heavy or light chains. Having confirmed binding to EGFR and Her2 and cytotoxicity of our AffiMabs, we analyzed apoptosis rate, receptor surface levels, phosphorylation levels of receptors and associated signaling pathways as well as differentially expressed genes on transcriptome level with the aim to elucidate the mode of action of our AffiMabs. RESULTS: The AffiMabs are able to simultaneously bind HER2 and EGFR and show increased cytotoxic effect compared to the original trastuzumab therapeutic molecule and, more importantly, even to the combination of trastuzumab and EGFR-targeting Affibody molecule. Analyzing the mode of action, we could show that bi-specific AffiMabs lead to reduced surface receptor levels and a downregulation of cell cycle associated genes on transcriptome level. CONCLUSION: Our study shows that transcriptome analysis can be used to validate the choice of receptor targets and guide the design of novel multi-specific molecules. The inherent modularity of the AffiMab format renders it readily applicable to other receptor targets.

DNA methylation disruption reshapes the hematopoietic differentiation landscape.

Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A) are frequently observed in hematological malignancies1-3 and clonal hematopoiesis4,5. Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A-mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif.

Impedance spectroscopy for in situ and real-time observations of the effects of hydrogen on nitrile butadiene rubber polymer under high pressure.

Nondestructive impedance spectroscopy (IS) was developed and demonstrated to detect the effects of hydrogen on nitrile butadiene rubber exposed to hydrogen gas (H2) at high pressures up to 10 MPa. IS was applied to obtain an in situ and real-time quantification of H2 penetration into and its desorption out of rubber under high pressure. The diffusion coefficients of H2 were also obtained from the time evolution of the capacitance, which were compared with those obtained by thermal desorption gas analysis. The in situ measurements of the capacitance and the dissipation factor under various pressures during cyclic stepwise pressurization and decompression demonstrated the diffusion behaviour of H2, the phase of the rubber under high pressure, the transport properties of H2 gas, and the physicochemical interaction between H2 and the rubber. These phenomena were supported by a COMSOL simulation based on the electric current conservation equation and scanning electron microscopy (SEM) observations.

Somatic mutations and cell identity linked by Genotyping of Transcriptomes.

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL.

Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.

Intratumor heterogeneity inferred from targeted deep sequencing as a prognostic indicator.

Tumor genetic heterogeneity may underlie poor clinical outcomes because diverse subclones could be comprised of metastatic and drug resistant cells. Targeted deep sequencing has been used widely as a diagnostic tool to identify actionable mutations in cancer patients. In this study, we evaluated the clinical utility of estimating tumor heterogeneity using targeted panel sequencing data. We investigated the prognostic impact of a tumor heterogeneity (TH) index on clinical outcomes, using mutational profiles from targeted deep sequencing data acquired from 1,352 patients across 8 cancer types. The TH index tended to be increased in high pathological stage disease in several cancer types, indicating clonal expansion of cancer cells as tumor progression proceeds. In colorectal cancer patients, TH index values also correlated significantly with clinical prognosis. Integration of the TH index with genomic and clinical features could improve the power of risk prediction for clinical outcomes. In conclusion, deep sequencing to determine the TH index could serve as a promising prognostic indicator in cancer patients.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells.

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level.

Establishment of a Patient-derived Xenograft for Development of Personalized HER2-targeting Therapy in Gastric Cancer.

BACKGROUND/AIM: To maximize success rate for development of HER2-targeted therapeutics, patient-derived xenograft (PDX) models reflecting HER2-positive gastric cancer (HER2+ GC) patients were established. MATERIALS AND METHODS: GC tissues obtained from surgery of GC patients were implanted into immune-deficient mice, and tumor tissue of HER2+ PDXs were verified of the patient-mimic HER2 expression by immunohistochemistry and explored for the feasibility by testing with Herceptin, the approved therapeutics and novel HER2 antibody therapeutics being developed. RESULTS: We obtained 5 cases of HER2+ GC PDX models reflecting patient's GC tumor, consisting of 2 cases of HER2 3+ and 2 cases of HER2 2+. Novel HER2 antibody displayed significantly improved anti-cancer efficacy in combination with Herceptin. CONCLUSION: The HER2+ GC PDX models were successfully established to be utilized for preclinical evaluation of HER2-targeting drugs and combined therapies for GC treatment, as an ideal platform of personalized tools for precision therapy.

Clinical Application of Targeted Deep Sequencing in Solid-Cancer Patients and Utility for Biomarker-Selected Clinical Trials.

Molecular profiling of actionable mutations in refractory cancer patients has the potential to enable "precision medicine," wherein individualized therapies are guided based on genomic profiling. The molecular-screening program was intended to route participants to different candidate drugs in trials based on clinical-sequencing reports. In this screening program, we used a custom target-enrichment panel consisting of cancer-related genes to interrogate single-nucleotide variants, insertions and deletions, copy number variants, and a subset of gene fusions. From August 2014 through April 2015, 654 patients consented to participate in the program at Samsung Medical Center. Of these patients, 588 passed the quality control process for the 381-gene cancer-panel test, and 418 patients were included in the final analysis as being eligible for any anticancer treatment (127 gastric cancer, 122 colorectal cancer, 62 pancreatic/biliary tract cancer, 67 sarcoma/other cancer, and 40 genitourinary cancer patients). Of the 418 patients, 55 (12%) harbored a biomarker that guided them to a biomarker-selected clinical trial, and 184 (44%) patients harbored at least one genomic alteration that was potentially targetable. This study demonstrated that the panel-based sequencing program resulted in an increased rate of trial enrollment of metastatic cancer patients into biomarker-selected clinical trials. Given the expanding list of biomarker-selected trials, the guidance percentage to matched trials is anticipated to increase. IMPLICATIONS FOR PRACTICE: This study demonstrated that the panel-based sequencing program resulted in an increased rate of trial enrollment of metastatic cancer patients into biomarker-selected clinical trials. Given the expanding list of biomarker-selected trials, the guidance percentage to matched trials is anticipated to increase.

Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer.

Single-cell transcriptome profiling of tumour tissue isolates allows the characterization of heterogeneous tumour cells along with neighbouring stromal and immune cells. Here we adopt this powerful approach to breast cancer and analyse 515 cells from 11 patients. Inferred copy number variations from the single-cell RNA-seq data separate carcinoma cells from non-cancer cells. At a single-cell resolution, carcinoma cells display common signatures within the tumour as well as intratumoral heterogeneity regarding breast cancer subtype and crucial cancer-related pathways. Most of the non-cancer cells are immune cells, with three distinct clusters of T lymphocytes, B lymphocytes and macrophages. T lymphocytes and macrophages both display immunosuppressive characteristics: T cells with a regulatory or an exhausted phenotype and macrophages with an M2 phenotype. These results illustrate that the breast cancer transcriptome has a wide range of intratumoral heterogeneity, which is shaped by the tumour cells and immune cells in the surrounding microenvironment.

Spatiotemporal genomic architecture informs precision oncology in glioblastoma.

Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. However, this proposition is complicated by spatial and temporal heterogeneity. Here we study genomic and expression profiles across 127 multisector or longitudinal specimens from 52 individuals with glioblastoma (GBM). Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, whereas geographically separated, multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated with genetic similarity, and multifocal tumors that are enriched with PIK3CA mutations have a heterogeneous drug-response pattern. We show that targeting truncal events is more efficacious than targeting private events in reducing the tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multisector biopsies can inform targeted therapeutic interventions for patients with GBM.

Molecular Evolution Patterns in Metastatic Lymph Nodes Reflect the Differential Treatment Response of Advanced Primary Lung Cancer.

Tumor heterogeneity influences the clinical outcome of patients with cancer, and the diagnostic method to measure the tumor heterogeneity needs to be developed. We analyzed genomic features on pairs of primary and multiple metastatic lymph nodes from six patients with lung cancer using whole-exome sequencing and RNA sequencing. Although somatic single-nucleotide variants were shared in primary lung cancer and metastases, tumor evolution predicted by the pattern of genomic alterations was matched to anatomic location of the tumors. Four of six cases exhibited a branched clonal evolution pattern. Lymph nodes with acquired somatic variants demonstrated resistance to the cancer treatment. In this study, we demonstrated that multiple biopsies and sequencing strategies for different tumor regions are required for a comprehensive understanding of the landscape of genetic alteration and for guiding targeted therapy in advanced primary lung cancer. Cancer Res; 76(22); 6568-76. ©2016 AACR.

Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma.

BACKGROUND: Intratumoral heterogeneity hampers the success of marker-based anticancer treatment because the targeted therapy may eliminate a specific subpopulation of tumor cells while leaving others unharmed. Accordingly, a rational strategy minimizing survival of the drug-resistant subpopulation is essential to achieve long-term therapeutic efficacy. RESULTS: Using single-cell RNA sequencing (RNA-seq), we examine the intratumoral heterogeneity of a pair of primary renal cell carcinoma and its lung metastasis. Activation of drug target pathways demonstrates considerable variability between the primary and metastatic sites, as well as among individual cancer cells within each site. Based on the prediction of multiple drug target pathway activation, we derive a combinatorial regimen co-targeting two mutually exclusive pathways for the metastatic cancer cells. This combinatorial strategy shows significant increase in the treatment efficacy over monotherapy in the experimental validation using patient-derived xenograft platforms in vitro and in vivo. CONCLUSIONS: Our findings demonstrate the investigational application of single-cell RNA-seq in the design of an anticancer regimen. The approach may overcome intratumoral heterogeneity which hampers the success of precision medicine.

Deciphering intratumor heterogeneity using cancer genome analysis.

Intratumor heterogeneity within individual cancer tissues underlies the numerous phenotypes of cancer. Tumor subclones ultimately affect therapeutic outcomes due to their distinct molecular features. Drug-resistant subclones are present at a low frequency in tissues at the time of biopsy, but can also arise as a result of acquired somatic mutations. A number of different approaches have been utilized to understand the nature of intratumor heterogeneity. Clonal analysis using whole exome or genome sequencing data can help monitor subclones in the context of tumor progression. Multiregional biopsies permit the molecular characterization of subclones within tumors. Deep sequencing has also provided researchers with the ability to measure the low allele fraction variant within a small number of cells. Ultimately, single-cell sequencing will enable the identification of every minor population within a tumor microenvironment. In the clinical context, the ability to identify and monitor the subclonal architecture of a tumor is valuable for the development of precise cancer therapeutic methods.

Identification of Distinct Tumor Subpopulations in Lung Adenocarcinoma via Single-Cell RNA-seq.

Single-cell sequencing, which is used to detect clinically important tumor subpopulations, is necessary for understanding tumor heterogeneity. Here, we analyzed transcriptomic data obtained from 34 single cells from human lung adenocarcinoma (LADC) patient-derived xenografts (PDXs). To focus on the intrinsic transcriptomic signatures of these tumors, we filtered out genes that displayed extensive expression changes following xenografting and cell culture. Then, we performed clustering analysis using co-regulated gene modules rather than individual genes to minimize read drop-out errors associated with single-cell sequencing. This combined approach revealed two distinct intra-tumoral subgroups that were primarily distinguished by the gene module G64. The G64 module was predominantly composed of cell-cycle genes. E2F1 was found to be the transcription factor that most likely mediates the expression of the G64 module in single LADC cells. Interestingly, the G64 module also indicated inter-tumoral heterogeneity based on its association with patient survival and other clinical variables such as smoking status and tumor stage. Taken together, these results demonstrate the feasibility of single-cell RNA sequencing and the strength of our analytical pipeline for the identification of tumor subpopulations.