New Biomarkers Of Response Research Articles

Abstract 6247: Lurbinectedin shows potent activity in all four molecular subtypes of small cell lung cancer (SCLC) and POU2F3 and SLFN11 are biomarkers for a better response

Abstract Background - SCLC is the most aggressive lung cancer type and with the worst prognosis. There are four molecular subtypes based on the high expression of distinct transcription factors and with different therapeutic vulnerabilities. However, all share transcriptional addiction as pathogenic mechanism. Lurbinectedin is a novel oncogenic transcription inhibitor, approved in the United States and other countries for the treatment of adult patients with metastatic SCLC with disease progression on or after platinum-based chemotherapy. The aim of this study was to analyze the activity of lurbinectedin in the different SCLC molecular subtypes and to investigate new biomarkers of response. Methods and Results - We have characterized a panel of 20 SCLC human cell lines based on the expression of ASCL1, NEUROD1, YAP1 and POU2F3, where lurbinectedin yielded a mean IC50 value of 6.52 nM, which is considerable greater than the activity exerted by topotecan, irinotecan, carboplatin, etoposide, olaparib, alisertib and navitoclax (IC50 100 µM-100 nM). Lurbinectedin potency is high in the four molecular subtypes, with IC50 values of 4.1, 14.9, 7.2, and 0.2 nM for SCLC-A, -N, -I and -P, respectively. However, high expression of POU2F3 correlated with better responses. In fact, mean IC50 was 0.28 nM for POU2F3high cells versus 12.1 nM for all POU2F3low cells (p=0.0443). Additionally, basal SLFN11 levels were evaluated, observing that SLFN11high cells responded better to lurbinectedin, with IC50 values of 1.1 nM versus 11.8 nM for SLFN11low (p=0.05). Likewise, lurbinectedin treatment induced greater antitumor activity in SLFN11high tumor-bearing mice (H526: T/C, 18% on day 11) than in SLFN11low tumor-bearing mice (H82: T/C, 65% on day 7) after intravenous treatment at 0.18 mg/kg (on days 0, 7 and 14). Finally, SLFN11 expression was evaluated by IHC in FFPE tumor samples from SCLC patients participating in a multicenter phase II clinical trial in advanced solid tumors (NCT02454972), which allowed lurbinectedin accelerated approval in this indication by FDA. Patients with higher expression of SLFN11 had a slightly better overall survival (OS at 6 months: 68.4% (<15%, N=20) vs. 98.7% (≥15%, N=20) p=0.0261)), especially in the refractory/resistant subgroup (OS at 6 months: 33.3% (<15%, N=9) vs. 100.0% (≥15%, N=6) p<0.0001). Conclusions - Lurbinectedin is highly effective in all molecular subtypes of SCLC in vitro and in vivo, with IC50 values at least two logs more potent than for other antitumoral agents and its activity is even greater in tumors with high POU2F3 expression and/or high SLFN11 expression. Citation Format: Marta Martínez Diez, Gema Santamaría Nuñez, María José Guillén, Daniel Rueda, Eva Maria Garrido-Martin, Pablo Avilés, Carmen Cuevas. Lurbinectedin shows potent activity in all four molecular subtypes of small cell lung cancer (SCLC) and POU2F3 and SLFN11 are biomarkers for a better response. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6247.

Prospects for using high-throughput sequencing methods to identify new biomarkers of response and resistance to antitumor therapy

High-throughput next-generation sequencing (NGS) technologies such as whole exome sequencing (WES) and bulk RNA sequencing (RNA-seq) allow identification of the new biomarkers of response and resistance to antitumor therapy. Retrospective studies have shown that the state of the tumor microenvironment (TME), identified via RNA-seq, is an independent prognostic and predictive biomarker. WES and RNA-seq technologies, along with classical immunohistochemistry, provide a comprehensive analysis of the tumor and TME. Affordability of high-throughput sequencing will enable personalization of antitumor pharmacotherapy.

Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small-cell lung cancer

BackgroundMost patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this...

Natural and Induced Tolerance to Hymenoptera Venom: A Single Mechanism?

Inducing tolerance in Hymenoptera-allergic patients, bee venom immunotherapy (BVIT) is a widely accepted method to treat severe allergy to bee stings. In order to increase the existing knowledge on the underlying immunological mechanisms and look for possible biomarkers predictive of efficacy, a group of 20 bee-venom-allergic patients (AG) were thoroughly examined during their first year of BVIT. In addition, the results of treated patients with those of an untreated group of 20 tolerant beekeepers (TG) who had previously shown a firm suppressor-regulatory profile were compared. Tolerance in AG patients was invariably associated with a significant regulatory response characterised by the expansion of Helios− subpopulation and increased IL-10, specific IgG4 (sIgG4), and kynurenine levels. Although specific IgE (sIgE) levels increased transiently, surprisingly, the T helper type 2 (Th2) population and IL-4 levels rose significantly after one year of immunotherapy. Thus, the picture of two parallel phenomena emerges: a tolerogenic response and an allergenic one. Comparing these results with those obtained from the TG, different immunological mechanisms appear to govern natural and acquired tolerance to immunotherapy. Of particular interest, the kynurenine levels and T regulatory (Treg) Helios− population could be proposed as new biomarkers of response to BVIT.

Abstract 2027: Spatial omics and multiplexed imaging to discover new biomarkers of response or resistance to immune checkpoint inhibitors (ICI) in advanced non-small cell lung cancer (NSCLC)

Abstract Introduction: Despite the impressive outcomes with ICI in NSCLC, only a minority of the patients show long-term benefit from ICI. While PD-L1 immunohistochemistry is an approved companion diagnostic test, it is neither sensitive nor specific. Here, we describe the use of spatial transcriptomics using the GeoMx Digital Spatial Profiler (DSP) as a discovery platform to find biomarkers for ICI response or resistance. Methods: Pre-treatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in two-fold redundancy. The human whole transcriptome, represented by 18000 genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the mRNAs present in each region of interest. Three molecularly defined tissue compartments, defined by fluorescence co-localization (tumor [panCK+], leukocytes [CD45+/CD68-], macrophages [CD68+]) were generated to assess mRNA. All statistical testing was performed using a two-sided significance level of α=0.05. Result: 54000 gene variables were generated per case, from them about 27000 were analyzed after removing targets with expression lower than a prespecified frequency. Expression distribution of EPCAM in tumor, PTPRC in leukocytes and CD68 in macrophages confirmed that DSP successfully profiled the molecular compartments. Differential gene expression (DEG) analysis was performed for 6-month clinical benefit across two distinct tumor TMA spots per patient. This resulted in a DEG list of about 250, 125 and 122 genes in CK, CD45 and CD68 compartment respectively. When we used the intersection of significantly associated with benefit genes the candidate list was reduced dramatically to 5, 10 and 10 distinct genes in CK (CYBA, ESD, SH3BGRL3, TOP2B, UFM1), CD45 (ATRN, DGAT1, DNAAF9, GMPS, IFT20, MPHOSPH6, PKP4, SOCS2, TFAP4, TGFB3) and CD68 (ANKS3, ARFRP1, CTSD, DPYD, GTF3C5, HS2ST1, KIAA0895L, PIGR, SFTPA2, YEATS4) compartment respectively. From them, using the Cox Proportional-Hazards Model we further identified CYBA, ESD and UFM1 in CK, DGAT1 and IFT20 in CD45 and ANKS3 and DPYD in CD68 to predict survival as well. Conclusions: Using DSP technology allows rapid, patient-specific assessment of the transcriptome in TMAs by in situ hybridization in spatially defined molecular compartments. Here we show a small set of candidate genes that are associated with outcome in this ICI-treated cohort. By intersecting two non-adjacent cores of the same patient tissue sample, we have begun to dissect tumor heterogeneity and pilot biomarker candidate information with unique molecularly defined compartments for tumor cells, lymphocytes, and macrophages. Results from this cohort may lead to a novel, spatially defined, transcriptomic approach for developing new biomarkers for immunotherapy. Citation Format: Myrto Moutafi, Sandra Martinez-Morilla, Rolando Garcia-Milian, Thazin Nwe Aung, Ioannis Vathiotis, Niki Gavrielatou, Vasiliki Xirou, Leonidas Salichos, David L. Rimm. Spatial omics and multiplexed imaging to discover new biomarkers of response or resistance to immune checkpoint inhibitors (ICI) in advanced non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2027.

Biomarkers of Response and Resistance to Immunotherapy in Microsatellite Stable Colorectal Cancer: Toward a New Personalized Medicine.

Simple SummaryImmune Checkpoint Inhibitors (ICIs) have demonstrated clinical efficacy in Microsatellite Instability High Colorectal Cancer (MSI-H CRC). However, in Microsatellite Stable (MSS) CRC, ICIs monotherapy provides limited clinical benefit. Therefore, efforts must be made to understand the highly heterogeneous CRC microenvironment and to find predictive biomarkers of response in order to adequately select CRC patients who may respond to ICIs-based therapies.Immune Checkpoint Inhibitors (ICIs) are well recognized as a major immune treatment modality for multiple types of solid cancers. However, for colorectal cancer (CRC), ICIs are only approved for the treatment of Mismatch-Repair-Deficient and Microsatellite Instability-High (dMMR/MSI-H) tumors. For the vast majority of CRC, that are not dMMR/MSI-H, ICIs alone provide limited to no clinical benefit. This discrepancy of response between CRC and other solid cancers suggests that CRC may be inherently resistant to ICIs alone. In translational research, efforts are underway to thoroughly characterize the immune microenvironment of CRC to better understand the mechanisms behind this resistance and to find new biomarkers of response. In the clinic, trials are being set up to study biomarkers along with treatments targeting newly discovered immune checkpoint molecules or treatments combining ICIs with other existing therapies to improve response in MSS CRC. In this review, we will focus on the characteristics of response and resistance to ICIs in CRC, and discuss promising biomarkers studied in recent clinical trials combining ICIs with other therapies.

Transient neural oscillations reveal new biomarkers for therapeutic transcranial magnetic stimulation for comorbid MDD and PTSD

Abstract Repetitive transcranial magnetic stimulation (TMS) is a therapy for major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). TMS effectiveness varies across patients and optimal protocols are unknown. Electroencephalography (EEG) examines brain dynamics associated with TMS often in highly averaged data (Zandvakili et al, 2019). In non-averaged signals, EEG oscillations may emerge as high power transients, coined “events” (Jones, 2016; Shin et al, 2017). We applied methods to analyze event features to describe biomarkers of TMS and their relationship to clinical outcomes. We collected resting 8-channel EEG before and after therapeutic TMS for 23 patients with comorbid MDD and PTSD targeting the left dorsolateral prefrontal cortex. Using our open-source toolbox (https://github.com/jonescompneurolab/SpectralEvents), we tested if resting state oscillations can be quantified as events in non-averaged data using 2-second windows. We assessed if event characteristics – event rate, power, duration, frequency span – changed after TMS or correlated with symptom improvement. Averaged omnibus power spectral density revealed peaks in frequency bands including delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz). Transient high-power events emerged from non-averaged data. Overall, frontal delta/theta and alpha event number and medial delta/theta event duration decreased after TMS (all p < 0.05). Pretreatment event characteristics correlated with subsequent clinical response. Frontal delta/theta event frequency span negatively correlated with MDD & PTSD improvement; medial alpha event power and duration positively correlated with MDD improvement, whereas medial alpha event rate and duration positively correlated with PTSD improvement; and frontal beta duration negatively correlated with PTSD improvement (all r2 > 0.15). Novel methods to characterize spectral events in non-averaged signals identified periods of high power activity in resting EEG data and revealed changes in event features potentially predictive of TMS response. EEG-recorded events ultimately may provide new biomarkers of response and a better mechanistic understanding of TMS. Keywords: Transcranial magnetic stimulation, Resting state EEG, Major depressive disorder, Post-traumatic stress disorder

Transcriptomic landscape of male and female reproductive cancers: Similar pathways and molecular signatures predicting response to endocrine therapy

Reproductive cancers in both genders represent serious health problems, whose incidence has significantly risen over the past decades. Although considerable differences among reproductive cancers exist, we aimed to identify similar signaling pathways and key molecular oncomarkers shared among six human reproductive cancers that can advance the current knowledge of cancer biology to propose new strategies for more effective therapies. Using a computational analysis approach, here we uncover aberrant miRNAs-mRNAs networks shared in six reproductive tumor types, and identify common molecular mechanisms strictly associated with cancer promotion and aggressiveness. Based on the fact that estrogenic and androgenic signaling pathways were most active in prostate and breast cancers, we further demonstrated that both androgen and estrogen deprivation therapy are capable of regulating the expression of the same key molecular sensors associated with endoplasmic reticulum dysfunction and cell cycle in these cancers. Overall, our data reveal a potential mechanistic framework of cellular processes that are shared among reproductive cancers, and particularly, highlight the importance of hormonal deprivation in breast and prostate cancers and potentially new biomarkers of response to these therapeutic approaches.

Targeting Cell Cycle in Breast Cancer: CDK4/6 Inhibitors.

Deregulation of cell cycle, via cyclin D/CDK/pRb pathway, is frequently observed in breast cancer lending support to the development of drugs targeting the cell cycle control machinery, like the inhibitors of the cycline-dependent kinases (CDK) 4 and 6. Up to now, three CDK4/6 inhibitors have been approved by FDA for the treatment of hormone receptor-positive (HR+), HER2-negative metastatic breast cancer. These agents have been effective in improving the clinical outcomes, but the development of intrinsic or acquired resistance can limit the efficacy of these treatments. Clinical and translational research is now focused on investigation of the mechanism of sensitivity/resistance to CDK4/6 inhibition and novel therapeutic strategies aimed to improve clinical outcomes. This review summarizes the available knowledge regarding CDK4/6 inhibitor, the discovery of new biomarkers of response, and the biological rationale for new combination strategies of treatment.

Abstract 6428: Imputing a more selective therapy: Identifying Wee1 and XPO1 inhibitors for TNBC

Abstract Clinical datasets often lack robust treatment information, and the information contained is necessarily limited to a single treatment paradigm. This hinders our ability to make the most use the information present in these datasets. However, our lab previously published on work that allows for the imputation of drug response from cell line screening datasets by building models between baseline gene expression of cell lines and that cell lines respective sensitivity to a particular drug. This, for example, allowed us to associate hundreds of drugs with both mutations and CNVs in TCGA that allowed us to recapitulate existing and identify new biomarkers of response. Our aim was to use adopt our computational framework for the purpose of drug repositioning by identifying trends between clinical subtypes of cancer and identify compounds imputed to be selective for that subtype. For this study, we chose to focus on triple-negative breast cancer (TNBC) since it is a clinically unmet need. We began by building unique drug-imputation models for all 545 drugs in the Cell Therapeutics Response Portal (Broad Institute) between cell line drug response and the cell line's RNA-Seq profile. Then we applied the models to the transcriptomic data in The Cancer Genome Atlas's (TCGA's) breast cancer cohort. After simple stratification and statistical testing, we selected two targets of interest based on their selective imputed scores for TNBC over the receptor-positive breast cancers: the Wee1 inhibitor AZD1775 and an XPO1 inhibitor. For both drugs we were able to validate our predictions using standard cross-validation approaches as well as investigating Sanger's Genomics of Drug Sensitivity in Cancer dataset. Additionally, we were able to capture biologically-relevant observations for Wee1 inhibition, such as enrichment for gene sets associated with the G2-M cell cycle checkpoint and an association between p53 mutations and increased efficacy of the Wee1 inhibitor. Additionally, using xenograft tumor growth assays as well as time-to-endpoint analysis, we were able to show that Wee1 inhibition with AZD1775 was able to inhibit tumor growth and increase survival of the mice, especially in combination with paclitaxel. For XPO1 inhibition, we were able to recapitulate strong inhibition of a panel of TNBC cell lines and work is currently ongoing to determine if similar analysis of gene sets and potential biomarkers of response is biologically meaningful. Overall, we believe these results indicate that computational methods can be employed to generate hypotheses for identifying selective or targeted agents for particular disease subtypes that could be explored in other cancer settings as well as supports the use for Wee1 and XPO1 inhibition as a potential therapeutic strategy for the treatment of triple-negative breast cancers. Citation Format: Robert F. Gruener, Montserrat Tijerina, Geoffrey L. Greene, R. Stephanie Huang. Imputing a more selective therapy: Identifying Wee1 and XPO1 inhibitors for TNBC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6428.

HRness in Breast and Ovarian Cancers.

Ovarian and breast cancers are currently defined by the main pathways involved in the tumorigenesis. The majority are carcinomas, originating from epithelial cells that are in constant division and subjected to cyclical variations of the estrogen stimulus during the female hormonal cycle, therefore being vulnerable to DNA damage. A portion of breast and ovarian carcinomas arises in the context of DNA repair defects, in which genetic instability is the backdrop for cancer initiation and progression. For these tumors, DNA repair deficiency is now increasingly recognized as a target for therapeutics. In hereditary breast/ovarian cancers (HBOC), tumors with BRCA1/2 mutations present an impairment of DNA repair by homologous recombination (HR). For many years, BRCA1/2 mutations were only screened on germline DNA, but now they are also searched at the tumor level to personalize treatment. The reason of the inactivation of this pathway remains uncertain for most cases, even in the presence of a HR-deficient signature. Evidence indicates that identifying the mechanism of HR inactivation should improve both genetic counseling and therapeutic response, since they can be useful as new biomarkers of response.

The Pros and Cons of Incorporating Transcriptomics in the Age of Precision Oncology.

The treatment of cancer continues to evolve toward personalized therapies based on individual patient and tumor characteristics. Our successes and failures in adopting a precision-oncology approach have demonstrated the utmost importance in identifying the proper predictive biomarkers of response. Until recently, most biomarkers were identified using immunohistochemistry for protein expression or single-gene analysis to identify targetable alterations. With the rapid propagation of next-generation sequencing to evaluate tumor tissue and "liquid biopsies," identification of genomic biomarkers is now standard, particularly in non-small cell lung cancer, for which there is now an extensive catalog of biomarker-directed therapies with more anticipated to come. Despite these great strides, it has also become apparent that using genomic biomarkers alone will be insufficient, as it has been consistently shown that at least one-half of patients who undergo tumor genomic profiling have no actionable alteration. This is perhaps to be expected given the remarkable breadth of nongenetic factors that contribute to tumor initiation and progression. Some have proposed that the next logical step is to use transcriptome profiling to define new biomarkers of response to targeted agents. Recently, results from the WINTHER trial were published, specifically investigating the use of transcriptomics to improve match rates over genomic next-generation sequencing alone. In this review, we discuss the complexities of precision-oncology efforts and appraise the available evidence supporting the incorporation of transcriptomic data into the precision-oncology framework in the historical context of the development of biomarkers for directing cancer therapy.

Genomic-based predictive biomarkers to anti-HER2 therapies: A combined analysis of CALGB 40601 (Alliance) and PAMELA clinical trials.

571 Background: In HER2-positive breast cancer, new biomarkers of response are needed in order to direct multi-agent anti-HER2 combinations towards patients in whom they are truly needed. CALGB 40601 and PAMELA trials tested neoadjuvant dual HER2 blockade and included gene expression analysis aimed to evaluate different genomic biomarkers of trastuzumab and/or lapatinib benefit. Methods: Gene expression by mRNA sequencing (RNAseq) was performed on 265 and 142 pre-treatment tumors of the CALGB 40601 and the PAMELA clinical trials respectively. Intrinsic subtypes were determined by nCounter PAM50-predictor on the PAMELA samples. A new HER2-positive specific gene-centering method was trained on the PAMELA RNAseq data, and showed a higher concordance with PAM50 predictions obtained from nCounter platform. This method was then applied to CALGB 40601 samples. Results: In the combined cohort, the subtype distribution was 10% Luminal A, 8% Luminal B, 62% HER2-enriched (HER2-E), 10% Basal and 10% Normal-like. The pCR rate was significantly higher in HER2-E vs. not HER2-E subtypes (48.6% vs. 20.7%; P &lt; 0.001). HER2-E subtype correlation, ERBB2 amplicon and B-cell genomic signatures were associated with pCR, while luminal signatures were associated with non-responders. In multivariate analysis HER2-E subtype, ERBB2 mRNA and IgG signature expression were independent predictors of response to paclitaxel + trastuzumab +/-lapatinib (OR = 1.98, OR = 1.51, OR = 1.48, respectively, P &lt;0.05). The event free survival analysis at 5 years in the CALGB 40601 cohort showed a benefit of dual vs single anti-HER2-blockade (HR 0.35, P &lt;0.05). Within the HER2-E, ERBB2-high and IgG–high subpopulations, there were also a benefit of dual vs. single anti-HER2 treatment (HR = 0.32, HR = 0.15, HR =0.15, respectively, P &lt;0.05). Conclusions: Intrinsic subtype, ERBB2 mRNA levels, and IgG genomic signature are independent predictive biomarkers of response in the combined cohort. The clinical implementation of these biomarkers could help to design future escalation/de-escalation clinical trials in the HER2-positive neoadjuvant setting. Support: U10CA180821, U10CA180882, U24CA196171, P50-CA58223, GSK, SPORE, BCRF and SEOM. https://acknowledgments.alliancefound.org .

Proliferative potential and resistance to immune checkpoint blockade in lung cancer patients

BackgroundResistance to immune checkpoint inhibitors (ICIs) has been linked to local immunosuppression independent of major ICI targets (e.g., PD-1). Clinical experience with response prediction based on PD-L1 expression suggests that other factors influence sensitivity to ICIs in non-small cell lung cancer (NSCLC) patients.MethodsTumor specimens from 120 NSCLC patients from 10 institutions were evaluated for PD-L1 expression by immunohistochemistry, and global proliferative profile by targeted RNA-seq.ResultsCell proliferation, derived from the mean expression of 10 proliferation-associated genes (namely BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, and TOP2A), was identified as a marker of response to ICIs in NSCLC. Poorly, moderately, and highly proliferative tumors were somewhat equally represented in NSCLC, with tumors with the highest PD-L1 expression being more frequently moderately proliferative as compared to lesser levels of PD-L1 expression. Proliferation status had an impact on survival in patients with both PD-L1 positive and negative tumors. There was a significant survival advantage for moderately proliferative tumors compared to their combined highly/poorly counterparts (p = 0.021). Moderately proliferative PD-L1 positive tumors had a median survival of 14.6 months that was almost twice that of PD-L1 negative highly/poorly proliferative at 7.6 months (p = 0.028). Median survival in moderately proliferative PD-L1 negative tumors at 12.6 months was comparable to that of highly/poorly proliferative PD-L1 positive tumors at 11.5 months, but in both instances less than that of moderately proliferative PD-L1 positive tumors. Similar to survival, proliferation status has impact on disease control (DC) in patients with both PD-L1 positive and negative tumors. Patients with moderately versus those with poorly or highly proliferative tumors have a superior DC rate when combined with any classification schema used to score PD-L1 as a positive result (i.e., TPS ≥ 50% or ≥ 1%), and best displayed by a DC rate for moderately proliferative tumors of no less than 40% for any classification of PD-L1 as a negative result. While there is an over representation of moderately proliferative tumors as PD-L1 expression increases this does not account for the improved survival or higher disease control rates seen in PD-L1 negative tumors.ConclusionsCell proliferation is potentially a new biomarker of response to ICIs in NSCLC and is applicable to PD-L1 negative tumors.

PO-404 Using functional genetic screens to understand cancer immune evasion

IntroductionWith the emerge of immunotherapy as an effective cancer therapy, there is also a growing need to identify new biomarkers of response as well as novel therapeutic targets. Functional CRISPR screens have proven to be an important tool to identify key genes in complex biological processes. We use an in vitro and in vivo CRISPR screening strategy to better understand how tumours evade the immune system.Material and methodsWe collected pre and post treatment biopsies from melanoma and lung cancer patients treated with an anti PD-1 inhibitor. Upon performing whole exome sequencing on biopsies from patients who progressed on therapy, we identified a list of candidate genes. We included genes that fell into one of the three categories: were mutated in more than one patient, were mutated only at relapse and had mutations in both alleles or had a heterozygous mutation at baseline and homozygous on progression.In addition, we also generated an adenovirus transformed mouse embryonic fibroblast cell line, which does not form tumours in the immunocompetent mice due to T-cell killing. We use this system do perform an in vivo CRISPR screen, investigating which genes are crucial for immune evasion.Results and discussionsWe have successfully generated a target gene list from sequences of patient biopsies. We have constructed a focused CRISPR library consisting of multiple gRNAs targeting each of those genes. This library will be used in a genetic screen in melanoma cells co-cultured with matched T-cells that recognise and eliminate the melanoma cells. Moreover, we will also use our in vivo adenoviral system to perform genome wide screens.ConclusionAfter the screening, we can cross validate hits from both platforms to identify robust hits. Furthermore, we can validate them in a bigger patient cohort to determine their potential as predictive biomarkers for immunotherapy response.

Abstract B48: Proteomic analysis of extracellular vesicles from resistant gastric cancer cell line

Abstract Background: Gastric cancer is the fourth most common cause of cancer death worldwide and one of the tumors with higher mortality rates in Brazil. Chemotherapy is one of the major treatments for gastric cancer, but drug resistance limits the effectiveness, resulting in treatment failure. The mechanisms of gastric cancer pathogenesis are largely unknown, as is what causes limitations in the personalized treatment. Neoadjuvant therapy has been largely applied in these tumors because it can improve tumor resectability and survival of patients. However, tumors can develop resistance during chemotherapy, or this resistance can be present intrinsically before chemotherapy. Indeed, mechanisms associated to chemotherapy resistance in gastric cancer are complex and multifactorial; understanding the variety of these factors that are involved in chemoresistance is of great relevance. Materials and Methods: Gastric adenocarcinoma cell line (AGS) was treated with increased concentration of 5-fluorouracil to generate a resistant cell (rAGS_FU). Extracellular vesicles (EVs) secreted from AGS and rAGS_FU cell lines were isolated by ultracentrifugation, quantified, and evaluated regarding their aggressiveness through invasion and colony assays. Proteomics analysis of EVs and secreting cells were performed to identify potential markers for chemotherapy resistance in gastric cancer cell lines. Results: We found proteins involved in resistance to chemotherapy upregulated in EVs derived from resistant cells; parental cells treated with EVs derived from resistant cells were able to promote high colony formation and increased invasion potential. Thus, cells resistant to chemotherapy have a more aggressive phenotype and are able to transfer these acquired characteristics to the nonresistant ones using EVs. We compared the proteomes of EVs derived from the two cell lines and revealed important pathways that can be associated with chemoresistance in gastric cancers. Conclusion: It is crucial to understand these chemoresistance mechanisms and develop efficient treatment strategies to overcome them. A deep investigation of these data is needed to understand and create new opportunities for the discovery of new biomarkers of response to chemotherapy in gastric cancers and contribute to the better understanding of the biologic role of molecules shuttled by EVs. Citation Format: Edson Kuatelela Cassinela, Grabriela Pintar Oliveira, Michele Christine Landemberger, Vilma Regina Martins. Proteomic analysis of extracellular vesicles from resistant gastric cancer cell line [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B48.

Abstract 4835: A new biomarker of response to 5-azacitidine therapy in MDS and AML patients: SIRPB1

Abstract Introduction: Myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) are a group of diseases of the elderly that initiates in a hematopoietic stem cell and are characterized by clonal hematopoiesis and uncertain prognosis, mostly due to cytogenetic background. In both diseases, 5-azacitidine (5-Aza) has been successful, inducing prolonged survival and delayed AML evolution. Aim: To identify the genes mostly predictive of treatment response, we use high-throughput genomic analysis (SNP arrays and/or NGS-RNA-seq and/or NGS-WES) in azacitidine-sensitive and resistant MDS/AML patients. Materials and Methods: NGS-WES or RNA seq HiSeq 2000 (Illumina) was positively done in 35/214 AML samples (16%). SNPs arrays (CytoScan HD Array, Affymetrix Inc.) was done in 125/214 AML samples (58%) and 18/32 MDS samples (56%) at diagnosis, then analyzed by Chromosome Analysis Suite (ChAS) v1.2 (Affymetrix Inc.), Nexus Copy Number™ v7.5 (BioDiscovery) and GeneGo MetaCore™ software. Results: We treated 246 adult patients (pts) with MDS or AML: 214 pts were AML and 32 were MDS with a median age of 59 and 70 years, respectively. Forty-five pts were treated with 5-Aza (32 MDS / 13 AML), while 201 AML were treated with conventional chemotherapy. Forty-five MDS/AML pts were treated with at least one complete cycle of 5-Aza (75 mg/sqm/daily). SNP arrays was done in 22/45 (49%), 13 pts were defined “insensitive/resistant”. Macroscopic CNAs affecting a complete chromosome or its arms were detected in 5 of 22 pts (23%), while classical cytogenetic was able to detect only two cases of trisomy 8 (9%), suggesting superiority of SNPs array for CNAs identifications. Chromosomic aberrations disease-related are more statistically frequent on pts “insensitive” versus pts. “sensitive” (64% vs. 35%) (p≤0.01). Moreover we found that from the median of chromosomic alterations lenghts (in kbp) the group of “insensitive” MDS/AML patients to 5-Aza therapy present more losses than “sensitive” ones. By Nexus Copy Number software, we identify 137 genes highly differentially gain (SIRPB1 and KIT with p ≤ 0.05) or loss (SIRPB1, LCE1C, BCAS1, EXD3 with p ≤ 0.05) or LOH between “insensitive” versus “sensitive” to 5-Aza (p ≤ 0.05). Among these genes, we focused on SIRPB1 (cytoband 20p13, 56Kbps), since it was loss on 14/22 (64%) “insensitive” pts (p = 0,023) and gain on 7/22 (32%) “sensitive” ones (p = 0,0324), respectively. SIRPB1 common deletion region length is 27 kbps and the common amplified region length is 30 kbps. By NGS-WES we analyzed 35/214 (16%) AML samples at diagnosis. We found mutations in SF3B1, NPM1, CBL, RUNX1, BCOR, KIT, GATA2, IDH2, KDM6A, KIAA1324L, PRIM2, RRN3, APOBR and again in SIRPB1 an heterozygous missense variant (rs45545343; p. H/D). Conclusions: We conclude that SIRPB1 is a promising marker of response to 5-Aza treatment in myelodysplastic syndromes and in acute myeloid leukemia. Citation Format: Viviana Guadagnuolo, Cristina Papayannidis, Ilaria Iacobucci, Giorgia Simonetti, Antonella Padella, Stefania Paolini, Mariachiara Abbenante, Sarah Parisi, Francesca Volpato, Chiara Sartor, Maria Chiara Fontana, Massimo Delledonne, Michele Malagola, Carla Filì, Domenico Russo, Sandro Grilli, Michele Cavo, Giovanni Martinelli. A new biomarker of response to 5-azacitidine therapy in MDS and AML patients: SIRPB1. [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 4835. doi:10.1158/1538-7445.AM2015-4835

Rheumatoid arthritis: Biomarkers of response to TNF inhibition in RA.

The quest for new biomarkers of response to therapies in rheumatoid arthritis (RA), particularly to TNF inhibitors, continues. Two recent studies add to this body of literature, finding both established and novel genetic variants that correlate with response to TNF inhibitors in RA.

Abstract 1897: Metformin treatment leads to the accumulation of lipid in breast cancer cell lines - a potential new biomarker of response and mechanism of action.

Abstract There is growing interest in the anticancer effect of the diabetes drug, metformin, and several clinical studies are underway worldwide. Metformin's anticancer effects are thought to be mediated by its activation of AMPK and subsequent downstream catabolic effects on protein and lipid metabolism pathways that are commonly dysregulated in cancer cells. We have used mass spectrometry techniques and stable isotopes to investigate the effects of metformin on breast cancer cell lipid metabolism. There was great variability in lipid metabolism response to 2mM metformin treatment in a panel breast cancer cell lines (MCF7, BT474, ZR-75-1, T47D MDA-MB-157, MDA-MB-468 and MDA-MB-231). Levels of stearic acid (p=0.019), palmitoleic acid (p=0.01), oleic acid (p=0.002), cis-vaccenic acid (p=0.003) increased 3-4 fold with metformin treatment in MCF7 cells but there was no significant change for MDA-MB-231 cells. 2mM Metformin decreased fatty acid β-oxidation of oleate 4-fold (p=0.03). Accumulation of de novo lipogenesis derived (p=0.004) and exogenous fatty acid (p=0.02) occurred in MCF7 cells but siRNA knockdown of AMPK did not abrogate these effects. A 3-fold decrease in the diglyceride to triglyceride ratio (p=0.02) suggested reduced lipolysis and inhibited adipose triglyceride lipase activity. Reduced incorporation of exogenous fatty acid into phospholipid was evident (p=0.002). Heterogeneity of lipid metabolism response correlated with effects on proliferation, oxygen consumption and mitochondrial morphology. Our data shows that metformin has marked effects on accumulation of fatty acid in breast cancer cells most likely due to reduced lipolysis and β-oxidation and these effects cannot be explained as a result of AMPK activation. This work will contribute to developing biomarkers for metformin's metabolic anticancer effect and our understanding of how to combine it with other therapies to exploit synthetic lethality. We have initiated a multicenter, phase II, single arm clinical study, to further characterise metformin influenced, cancer relevant metabolic pathways. We will look to assess the correlation between metabolic biomarkers, including the use of mass spectrometry and gas chromatography analysis of tissue samples, and metabolic response using 18F-FDG PET-CT scans. Citation Format: Simon Lord, Jennifer Collins, Barbara Fielding, Neel Patel, Fergus Gleeson, Adrian Harris, Fredrik Karpe. Metformin treatment leads to the accumulation of lipid in breast cancer cell lines - a potential new biomarker of response and mechanism of action. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1897. doi:10.1158/1538-7445.AM2013-1897

A phase II study of PXD101 (belinostat) in relapsed and refractory aggressive B-cell lymphomas (rel/ref ABCL): SWOG S0520.

e18536 Background: The mechanism of action of histone deacetylase inhibitors (HDACI) in lymphomas is unknown. Loss of major histocompatibility Class II antigens (MHC II) in diffuse large B-cell lymphomas (DLBCL) is associated with decreased tumor infiltrating T lymphocytes (TIL) and poor survival. Transcription of MHC II is controlled by CIITA, which is itself regulated by histone acetylation, We hypothesized that PXD101 (belinostat), an HDACI, would increase MHC II expression in tumor cells, enhance immunosurveillance and improve outcome. Methods: Theprimary objective was to evaluate response rate and toxicity of PXD101 in patients (pts) with rel/ref ABCL with up to 5 prior chemotherapy regimens. Secondary objectives were to estimate the 6-month progression-free survival (PFS) and to assess MHC II and TIL. In a two-stage design, if at least 1 response was observed in the first 20 pts, another 20 pts would be accrued. PXD101 was administered at 1000 mg/m2 IV days 1-5 of 21-day cycle for up to 2 years. Results: The study was closed due to lack of response in the first stage. Of 22 pts enrolled, 19 were evaluable. Median age was 69, and median number of prior treatments was 3 (range 1-4). 18 pts had DLBCL and 1 had B-cell lymphoma, unclassifiable. Grade 4 toxicities were fatigue and muscle weakness (1) and lymphopenia (1). Despite initially finding no responses, 2 partial responses (PR) were observed at 5 and 13 months after registration, for an overall response rate (95% CI) of 10.5% (1.3-33.1%); 3 pts had stable disease (SD), lasting 4.7, 30.4+, and 40.7+ months. With a minimum follow-up of 2.0 yrs, median and 6-month PFS are 2.1 months (1.3-3.8) and 21.1% (6.6-41.0%); median and 6-month overall survival are 13.4 months (95% CI not yet estimable) and 57.9% (33.2-76.3%), respectively. Conclusions: Despite early closure, delayed PR was seen in 2 of 19 pts, and 2 pts had SD lasting 30.4+ and 40.7+ months. Therefore 4 pts (21%) who did not achieve complete response, very unusually, have not progressed for ≥2.0 yrs. Standard chemotherapy response assessment may not be appropriate for HDACI, which may require development of new biomarkers of response. Further work focuses on combining HDACI with standard chemotherapy.