Abstract 3125: TCR specificity prediction of circulating T cells and TILs in personalized adoptive neoTCR T cell therapy

Background: Adoptive T-cell therapies would benefit from accurate computational prediction of T cell receptor (TCR) specificity to its target antigen. Despite the diversity of complementarity determining region (CDR) among T cells, many sequence features of CDRs are conserved. Conserved CDR sequences allow for shared specificity, that is, recognition of the same antigen, potentially increasing the pool of candidate TCRs available for treating patients. Utilizing sequence similarity, enrichment of V-genes, CDR lengths, and evidence of clonal expansion, several computational algorithms have been developed to predict the specificity of TCRs. Using neoantigen-specific TCRs (neoTCRs) in our phase 1 clinical trial (NCT039703820), we investigated the shared specificity of TCRs in the context of personalized autologous T cell therapy for cancer patients.

Methods: Leveraging a high throughput TCR discovery and validation platform, neoantigen-specific T cells were isolated from patient peripheral blood mononuclear cells (PBMCs) and their neoTCR sequences were identified. RNA-seq was performed on tumor biopsies and TCR sequences derived from tumor-infiltrating lymphocytes (TILs) were extracted using MiXCR software. TCR specificity algorithms TCRdist3, GLIPH2, and TCRmatch were then used to identify specificity groups within and between neoTCR sequences derived from patient PBMCs, TCR sequences derived from TILs, and publicly available TCR sequences of known specificities.

Results: NeoTCRs identified during our phase 1 clinical trial and their known neoantigens provided an experimentally validated benchmark for testing accuracy of TCR specificity prediction. TCR specificity algorithms accurately clustered neoTCR β chains into groups of shared antigen specificity. TCR chain sequences detected from TILs with high similarity to TCR sequences of neoTCRs from PMBCs were found, suggesting shared antigen specificity between circulating T cells and those found in the tumor. In addition, TCR specificity algorithms identified a public TCR sequence known to recognize an HPV-derived epitope presented by HLA-A*02:01 with high similarity to a TCR sequence identified in a tumor biopsy of an HPV16+ HLA-A*02:01+ patient with head and neck cancer.

Conclusion: Neoantigens and their associated neoTCRs identified by our TCR discovery and validation platform can be used as a benchmark for TCR specificity prediction algorithms. TCR specificity algorithms provide insight into TCRs with predicted shared specificity in the blood and within the tumor. Accurate identification of TIL TCRs with shared specificity to neoTCRs could inform on tumor trafficking and aid in therapeutic product selection. Similarly, accurate specificity matching of TIL TCRs to public TCRs with known targets could aid in identification of efficacious targets within the tumor.

Citation Format: Tyler Borrman, Eric Stawiski, Zheng Pan, Chad Smith, Susan Foy, Stefanie J. Mandl. TCR specificity prediction of circulating T cells and TILs in personalized adoptive neoTCR T cell therapy [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 3125.

Non-viral precision T cell receptor replacement for personalized cell therapy

T cell receptors (TCRs) enable T cells to specifically recognize mutations in cancer cells1-3. Here we developed a clinical-grade approach based on CRISPR-Cas9 non-viral precision genome-editing to simultaneously knockout the two endogenous TCR genes TRAC (which encodes TCRα) and TRBC (which encodes TCRβ). We also inserted into the TRAC locus two chains of a neoantigen-specific TCR (neoTCR) isolated from circulating T cells of patients. The neoTCRs were isolated using a personalized library of soluble predicted neoantigen-HLA capture reagents. Sixteen patients with different refractory solid cancers received up to three distinct neoTCR transgenic cell products. Each product expressed a patient-specific neoTCR and was administered in a cell-dose-escalation, first-in-human phase I clinical trial ( NCT03970382 ). One patient had grade 1 cytokine release syndrome and one patient had grade 3 encephalitis. All participants had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease and the other eleven had disease progression as the best response on the therapy. neoTCR transgenic T cells were detected in tumour biopsy samples after infusion at frequencies higher than the native TCRs before infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs that recognize mutational neoantigens. Moreover, simultaneous knockout of the endogenous TCR and knock-in of neoTCRs using single-step, non-viral precision genome-editing are achieved. The manufacture of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene-edited neoTCR T cell products and the ability of the transgenic T cells to traffic to the tumours of patients are also demonstrated.

Abstract P3-08-04: Discovery of cancer genes and pathways operative in PI3K-activated mammary cancer reveals clinically relevant genotype-phenotype correlations

Human breast cancer (BRCA) shows tremendous genomic, gene expression, clinical, and phenotypic heterogeneity. Known driver gene alterations can only explain a portion of this heterogeneity, some of which likely arise from variation in the target cell for transformation, in addition to incompletely understood gene copy number and epigenetic alterations. These factors are difficult to identify with certainty using human patient samples due to widely varying germline genetic backgrounds, thousands of gene copy and epigenetic changes per sample, and, unknown target cell transformation. Activating mutations in the p110α catalytic subunit of PI3K are one of the most common genetic alterations in human BRCA. Here, we report results from two Sleeping Beauty (SB) transposon-accelerated mouse models of Pik3ca-mutant mammary cancer showing how genotype-phenotype correlations can be drawn providing strong candidates for mediating tumor phenotypes, including estrogen-receptor (ER)-dependent gene expression, high cell cycle activity, and immune cell exclusion. We used SB transposon mutagenesis in mice on a Pik3caH1047R activated mutant background to model mammary cancer development in two different mammary epithelial compartments. Both the target cell for mutagenesis and the specific transposon-induced mutations correlated with specific tumor phenotypes, including whether the tumors were ER positive or negative. RNA sequencing of tumors revealed novel genotype-phenotype correlations implicating specific transposon-altered gene drivers of high cell cycle activity, ER-dependent gene expression, and white blood cell exclusion from the tumor. Many transposon-implicated genes are altered at the gene copy number or epigenetic/methylation level in human BRCA, and several were functionally validated. These models provide a source of genetically heterogenous mouse mammary tumors with a uniform initiating mutation, Pik3caH1047R, useful for identifying cooperating pathways and drivers of specific tumor phenotypes.

Citation Format: Morito Kurata, Emiily Pope, Jingmin Shu, Wenlin Yuan, Wendy Hudson, Mark Sokolowski, Setareh Bagherzadeh, Zora Modrusan, Eric Stawiski, Steffen Durinck, Sekar Seshigiri, Aaron Sarver, Nuri Temiz, David Largaespada. Discovery of cancer genes and pathways operative in PI3K-activated mammary cancer reveals clinically relevant genotype-phenotype correlations. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-04.

Abstract 563: Circulating tumor-specific T cells preferentially recognize patient-specific mutational neoantigens and infrequently recognize shared cancer driver mutations

Background: Due to a lack of prior technologies able to generate a landscape analysis of mutational neoantigen-HLA class I complex T cell recognition, it is unclear how the frequency of T cell receptors (TCR) against patient-specific mutations compares to shared oncogenic mutations.

Methods: We used the imPACT Isolation Technology®, which allows the selective capture of cancer-specific CD8 T cells from the blood of cancer patients at frequencies as low as 1 in 300K CD8 T cells. This TCR isolation platform is based on whole exome sequencing of a tumor and paired normal tissue control for the identification of non-synonymous mutations, including mutations in cancer driver genes (e.g., p53, KRAS, PI3KCA or HRAS). Bioinformatic algorithms were used to predict potential HLA-binding neoantigens (neoAg) in context of the patient’s HLA class I haplotype. A library of multimerized and barcoded predicted neoAg peptide-HLA molecules were generated to interrogate patient CD8 T cells. The paired αβ-TCR sequences were derived from the single cell sorted T cells. TCRs from antigen experienced CD8 T cell were functionally validated by generating T cells expressing neoTCRs, using non-viral precision gene editing to insert the transgenic TCR chains into the endogenous TRAC locus. We previously showed that all (40/40) TCRs isolated using this approach, reacted to patient-matched cancer cell lines (Puig Saus et al. AACR 2020).

Results: Neoantigen-specific T cells isolated from the peripheral blood of 243 patients with melanoma, bladder, endometrial, ovarian, colorectal, head and neck, urothelial and breast cancers were analyzed For each patient, an average of 352 neoAg-HLA capture complexes were predicted. Across all patients 58,058 neoAg-HLA complexes were manufactured, spanning 8,804 unique mutations. Among these, only about 2% represented known oncogene driver mutations. The predicted peptide-HLA binding affinity for cancer driver mutations was significantly lower (P<0.001) compared to patient-specific neoAg. Remarkably, functional characterization of 206 TCRs showed that most TCRs (93.7%) recognized patient-specific neoAg. Despite the low percentage of neoAg-HLA capture complexes covering oncogene driver mutations (~ 2%), 6.3% of TCRs (13) targeted known cancer driver proteins. Primary human T cells were then engineered to express each TCR. TCR T cells became functionally activated only when exposed to the cognate antigen, irrespective of whether they target neoAg or cancer driver mutations, confirming the high degree of specificity of the isolated TCRs.

Conclusion: A landscape analysis of neoAg-specific TCRs recognizing mutations in cancer has revealed that most T cells recognizing neoantigen-HLA complexes are specific for private mutations in each cancer, though low frequencies of TCR targeting driver mutations can still be identified.

Citation Format: Barbara Sennino, Jyoti Mathur, Eva Huang, Andrew Conroy, Marc Ting, Benjamin Yuen, Zheng Pan, Eric Stawiski, Stefanie Mandl. Circulating tumor-specific T cells preferentially recognize patient-specific mutational neoantigens and infrequently recognize shared cancer driver mutations [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 563.

Abstract 1213: Uncovering HLA loss of heterozygosity and allelic imbalance in cancer for the improvement of personalized neoTCR immunotherapy with PACT-ESCAPE

Introduction: PACT Pharma is a clinical-stage adoptive cell therapy company that develops personalized neoTCR-T cells using a state-of-the-art approach to discover and validate predicted neoepitopes and their cognate T cell receptors (clinical trial NCT03970382). An important mechanism of resistance to adoptive cell therapy targeting tumor-specific neoantigens is the genetic loss of human leukocyte antigen (HLA) alleles or alterations in HLA expression in tumor cells. Therapies targeting neoantigens presented by HLA alleles that have either been deleted, mutated or are strongly downregulated are likely to lack efficacy due to the absence or reduction of epitope presentation. Surveying neoepitope presentation escape mechanisms is key for personalized immunotherapy.

Methods: PACT Pharma has developed PACT-ESCAPE, a method that integrates DNA and RNA sequencing data to quantify allelic imbalance at HLA loci, including the most extreme case of loss of heterozygosity (LOH). Allelic imbalance is first determined at the DNA level by determining the patient’s maternal and paternal haplotypes across chromosome 6p to infer their copy number states. Twenty-six HLA Class I and II loci from chromosome 6 are then genotyped at high resolution, enabling accurate assignment of copy number states to the patient’s alleles, including any alleles that have been deleted in the tumor. Unlike other currently available methods, PACT-ESCAPE also measures the relative RNA expression of HLA alleles to provide an orthogonal estimate of allelic imbalance across chromosome 6 and support loss of heterozygosity calls made at the DNA level. Presentation machinery genes are also surveyed for loss of function mutations. To benchmark PACT-ESCAPE, we compared loss of heterozygosity calls at HLA-A, HLA-B, and HLA-C between our method and a previously published DNA-based HLA LOH classifier for 17 samples for which we had matched tumor/normal whole exome sequencing.

Results: We found 100% concordance between PACT-ESCAPE and the benchmark, with four samples showing LOH at HLA-A, HLA-B, and HLA-C at the DNA level. Next, we evaluated RNA sequencing from tumor samples and confirmed that the relative expression of the lost allele compared to the kept allele was lower when LOH was called. High levels of allelic imbalance in gene expression, however, were not unique to samples with LOH, suggesting that differential expression of HLA alleles might also be an important contributor to immune escape in cancer.

Conclusions: Evaluation of allelic imbalance in DNA copy number and RNA expression in PACT-ESCAPE provides new insights into immune escape in cancer. Adoptive cell therapy targeting neoantigens will benefit by enabling the accurate selection of targets most likely to be presented by the tumor.

Citation Format: Chad C. Smith, Yan Ma, Katie Campbell, Zheng Pan, Eric Stawiski. Uncovering HLA loss of heterozygosity and allelic imbalance in cancer for the improvement of personalized neoTCR immunotherapy with PACT-ESCAPE [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 1213.

RTK-Dependent Inducible Degradation of Mutant PI3Kα Drives GDC-0077 (Inavolisib) Efficacy

PIK3CA is one of the most frequently mutated oncogenes; the p110a protein it encodes plays a central role in tumor cell proliferation. Small-molecule inhibitors targeting the PI3K p110a catalytic subunit have entered clinical trials, with early-phase GDC-0077 studies showing antitumor activity and a manageable safety profile in patients with PIK3CA-mutant breast cancer. However, preclinical studies have shown that PI3K pathway inhibition releases negative feedback and activates receptor tyrosine kinase signaling, reengaging the pathway and attenuating drug activity. Here we discover that GDC-0077 and taselisib more potently inhibit mutant PI3K pathway signaling and cell viability through unique HER2-dependent mutant p110a degradation. Both are more effective than other PI3K inhibitors at maintaining prolonged pathway suppression. This study establishes a new strategy for identifying inhibitors that specifically target mutant tumors by selective degradation of the mutant oncoprotein and provide a strong rationale for pursuing PI3Kα degraders in patients with HER2-positive breast cancer. SIGNIFICANCE: The PI3K inhibitors GDC-0077 and taselisib have a unique mechanism of action; both inhibitors lead to degradation of mutant p110a protein. The inhibitors that have the ability to trigger specific degradation of mutant p110a without significant change in wild-type p110a protein may result in improved therapeutic index in PIK3CA-mutant tumors.See related commentary by Vanhaesebroeck et al., p. 20.This article is highlighted in the In This Issue feature, p. 1.

820 Machine learning significantly improves neoantigen-HLA predictions utilizing > 26,000 data points from the PACTImmuneTM Database

Background

PACT Pharma has developed a state-of-the-art approach to validate predicted neoepitopes (neoEs) and their cognate T cell receptors (neoTCRs) by capturing neoepitope-specific T cells from peripheral blood. This neoTCR discovery and validation process is being applied in clinical trial (NCT03970382) evaluating personalized neoTCR-T cell therapy to treat patients across eight solid tumor types. Extensive pre-, on- and post-treatment data related to this trial has been accumulated in the PACTImmune Database (PIDB) which represents a growing data asset for patient-specific tumor immunogenicity in solid tumors. Here we present a specific use case of applying machine learning (ML) to significantly improve neoE-HLA predictions and further model anticipated improvements of TCR capture as a direct consequence.

Methods

PACT has developed capabilities for high-throughput manufacturing of single polypeptide (comPACT protein) which consists of the predicted neoE peptide together with Beta-2-Microglobulin and the HLA heavy chain. comPACT molecules are considered successfully produced when protein yields reach concentrations >1uM. Data used for this study consisted of >26000 neoE-HLA predictions for 62 different HLA alleles. We applied ML to learn patterns that are predictive of neoE-HLAs that can be successfully produced as comPACTs, using scikit-learn and XGBoost. Data was first split into training and testing data. Models were trained on training data and model hyperparameters were tuned using 5-fold cross validation (5xCV). The performance of the models during 5xCV and on test data was measured using the area under the receiver operating characteristic curve (AUC). We additionally performed experimental prospective validation of the models. To do this, 603 neoE-HLAs (from 7 previously unseen cancer samples) were selected for comPACT production using netMHCpan4.1 and the newly trained models.

Results

The mean AUC for the 5xCV of the selected models ranged from 0.75 to 0.86 depending upon the HLA allele (SD <0.05 for every model). The AUC on the test data ranged from 0.75 to 0.92 (median = 0.85). Prospective validation resulted on average in a 22% higher success rate (range 11%–39%) using the new models as compared to the netMHCpan4.1 predictions. This is expected to result in increased capture of neoepitope-specific CD8+ T cells as the PIDB indicates that 3.2% of the successful comPACTs result in validated neoTCRs.

Conclusions

PIDB based ML predictions of neoE-HLAs led to a significant increase in TCR-capturing comPACT success rates. Because of this work, it is predicted both neoE-specific CD8+ T cell capture and actionable neoTCR options will increase per patient.

Abstract 2177: Tumor neoantigen profiling with validated patient-specific TCR characterization to improve neoepitope prediction

PACT Pharma has developed an ultra-sensitive approach to validate predicted neoantigens and the cognate T cell receptors (neoTCRs) from tumor specific somatic mutations by capturing neoantigen-specific T cells from peripheral blood. This process is used in clinical trials (NCT03970382) of personalized neoTCR-T therapy for persons with solid cancers.

Using the state of the art prediction pipeline and screening process, more than one hundred twenty neoantigens were predicted from 5 type of solid cancers that were validated by characterizing cognate T cells and their close to 200 unique TCRs captured from the blood of the same individual. These validated neoepitopes of 8 to 11 amino acids represent broad HLA class I coverage with &gt;30 alleles to date. Our analysis revealed that mutations can occur in all positions within the epitopes. Epitope immunogenicity is potentially affected by different mechanisms including mutation position, agretopicity, as well as HLA interacting positions and/or by interactions between mutated residues and its cognate TCRs. It was observed that these validated neoepitopes comprise broad ranges of predicted HLA binding affinities, stability, and neoantigen expression levels. The analysis presented here offers insights to enable machine learning to advance rules for epitope selection and prioritization that may be important for immunological approaches to address a broad range of diseases, including cancer.

Citation Format: Zheng Pan, Olivier Dalmas, Songming Peng, Kyle Jacoby, Barbara Sennino, Yan Ma, Chad Smith, Amin Momin, Allison Xu, Katharine Heeringa, Jonathan Johnston, Duo An, Boi Quach, William Lu, Diana Nguyen, Andrew Conroy, Bhamini Purandare, Eva Huang, Eric Stawiski, Alex Franzusoff, Stefanie Mandl. Tumor neoantigen profiling with validated patient-specific TCR characterization to improve neoepitope prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2177.

An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

By leveraging tumorgraft (patient-derived xenograft) RNA-sequencing data, we developed an empirical approach, DisHet, to dissect the tumor microenvironment (eTME). We found that 65% of previously defined immune signature genes are not abundantly expressed in renal cell carcinoma (RCC) and identified 610 novel immune/stromal transcripts. Using eTME, genomics, pathology, and medical record data involving >1,000 patients, we established an inflamed pan-RCC subtype (IS) enriched for regulatory T cells, natural killer cells, TH1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. IS is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. The IS subtype correlated with systemic manifestations of inflammation such as thrombocytosis and anemia, which are enigmatic predictors of poor prognosis. Furthermore, IS was a strong predictor of poor survival. Our analyses suggest that tumor cells drive the stromal immune response. These data provide a missing link between tumor cells, the TME, and systemic factors.Significance: We undertook a novel empirical approach to dissect the renal cell carcinoma TME by leveraging tumorgrafts. The dissection and downstream analyses uncovered missing links between tumor cells, the TME, systemic manifestations of inflammation, and poor prognosis. Cancer Discov; 8(9); 1142-55. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1047.

Abstract LB-331: Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations

Malignant pleural mesothelioma (MPM) is an aggressive cancer arising from the mesothelial cells of the pleura. About 80% of mesothelioma cases are linked to asbestos exposure, while the remainder may be related to prior chest radiation, genetic predisposition or spontaneous occurrence.

We analyzed transcriptomes (n = 211), whole exomes (n = 99), and targeted exomes (n = 103) from 216 malignant pleural mesothelioma (MPM) tumors. Four distinct molecular subtypes, sarcomatoid (S), epithelioid (E), biphasic-E, and biphasic-S were identified using RNA-seq data. Using exome analysis we found BAP1, NF2, TP53, SETD2, DDX3X, ULK2, RYR2, CFAP45, SETDB1, and DDX51 to be significantly mutated MPM genes. We identified recurrent mutations in several genes including splice complex factor SF3B1 (∼2% [4/216]) and TRAF7 (∼2% [5/216]). SF3B1 mutant samples showed a distinct splicing profile compared to wild-type tumors. Mutations in TRAF7 occurred primarily in the WD40 domain and except in one case were mutually exclusive with NF2 mutations. We found recurrent gene fusions and splice alterations to be frequent mechanisms for inactivation of NF2, BAP1 and SETD2. We analyzed the tumors for infiltrating immune cells and found that M2 macrophage to T-cell ratio was predictive of reduced overall survival. Further we found sarcomatoid subtype had a significantly higher level of PD-L1 expression suggesting that this group might be prioritized for checkpoint inhibitor therapy. Integrated analysis of alterations identified changes in Hippo, mTOR, Histone methylation, RNA helicase and p53 signaling pathways in MPMs.

Overall our study significantly expands on the previous genomic studies and provides a comprehensive genomics profile of mesothelioma and identifies several previously unknown alterations and biological pathways that are potential targets for drug discovery and treatment. Incorporating genomic analysis for detection of actionable alterations as part of MPM patient care will help in developing rational individualized therapy.

Citation Format: Somasekar Seshagiri, Eric Stawiski, Leonard Goldstein, Steffen Durinck, Zora Modrusan, Florian Gnad, Thong T. Nguyen, Bijay Jaiswal, Assunta De Rienzo, William Richards, Raphael Bueno. Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations. [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 LB-331.

Abstract 4428: Oncogenic ERBB3 mutations in human cancers

The human epidermal growth factor receptor (HER) family of tyrosine kinases are deregulated in multiple cancers either through amplification, overexpression or mutation. ERBB3/HER3, the only ERBB family member with an impaired kinase domain, upon ligand binding heterodimerizes with ERBB2 to promote signaling. While amplification and overexpression of ERBB3 is observed in some cancers, occurrence and relevance of ERBB3 somatic mutations in oncogenesis is not established. Here we report the identification of ERBB3 somatic mutations in ∼11% of colon and gastric cancers. We found that the ERBB3 mutants together with ERBB2 promote oncogenic signaling and transformed colonic and breast epithelial cells in a ligand independent manner. Further, we found that multiple target therapeutics that acts on ERBB3, ERBB2 or their downstream signaling components are effective in blocking ERBB3-mutant mediated oncogenic signaling and disease progression in vivo. Identification of activating ERBB3 mutations along with the established contribution of ERBB3 to acquired resistance to EGFR/ERBB2-targeted drugs provides a rational to therapeutically target ERBB3.

Citation Format: Bijay S. Jaiswal, Noelyn M. Kljavin, Eric Stawiski, Steffen Durinck, Subhra Chaudhuri, Charles Eigenbrot, Gabriele Schaefer, Frederic J. de Sauvage, Somasekar Seshagiri. Oncogenic ERBB3 mutations in human cancers. [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 4428. doi:10.1158/1538-7445.AM2014-4428

Identification of mutant K-Ras-dependent phenotypes using a panel of isogenic cell lines

To assess the consequences of endogenous mutant K-Ras, we analyzed the signaling and biological properties of a small panel of isogenic cell lines. These include the cancer cell lines DLD1, HCT116, and Hec1A, in which either the WT or mutant K-ras allele has been disrupted, and SW48 colorectal cancer cells and human mammary epithelial cells in which a single copy of mutant K-ras was introduced at its endogenous genomic locus. We find that single copy mutant K-Ras causes surprisingly modest activation of downstream signaling to ERK and Akt. In contrast, a negative feedback signaling loop to EGFR and N-Ras occurs in some, but not all, of these cell lines. Mutant K-Ras also had relatively minor effects on cell proliferation and cell migration but more dramatic effects on cell transformation as assessed by growth in soft agar. Surprisingly, knock-out of the wild type K-ras allele consistently increased growth in soft agar, suggesting tumor-suppressive properties of this gene under these conditions. Finally, we examined the effects of single copy mutant K-Ras on global gene expression. Although transcriptional programs triggered by mutant K-Ras were generally quite distinct in the different cell lines, there was a small number of genes that were consistently overexpressed, and these could be used to monitor K-Ras inhibition in a panel of human tumor cell lines. We conclude that there are conserved components of mutant K-Ras signaling and phenotypes but that many depend on cell context and environmental cues.

Mutational pathways and genetic barriers to CXCR4-mediated entry by human immunodeficiency virus type 1

To examine mutational pathways that lead to CXCR4 use of HIV-1, we analyzed the genotypic and phenotypic characteristics of envelope sequences from a large panel of patient virus populations and individual clones containing different V3 mutations. Basic amino acid substitutions at position 11 were strong determinants of CXCR4-mediated entry but required multiple compensatory mutations to overcome associated reductions in infectivity. In contrast, basic amino acid substitutions at position 25, or substitutions at positions 6-8 resulting in the loss of a potential N-linked glycosylation site, contributed to CXCR4-mediated entry but required additional substitutions acting cooperatively to confer efficient CXCR4 use. Our assumptions, based upon examination of patient viruses, were largely confirmed by characterizing the coreceptor utilization of five distinct panels of isogenic envelope sequences containing V3 amino acid substitutions introduced by site-directed mutagenesis. These results further define the mutational pathways leading to CXCR4 use and their associated genetic barriers.

Principal component analysis of general patterns of HIV-1 replicative fitness in different drug environments

To detect general patterns and temporal trends of HIV-1 resistance, we apply principal component analysis (PCA) to in vitro fitness data. Twenty-eight thousand virus samples, obtained between 2002 and 2008, were assayed for fitness in 16 to 21 selective environments. Fitness measurements are based on replication capacity (RC), which quantifies in vitro viral replication in a single cycle of infection. RC is determined both in the absence of drugs and in the presence of 6-7 nucleoside analog reverse transcriptase inhibitors (NRTIs), 3-4 non-nucleoside reverse transcriptase inhibitors (NNRTIs), and 6-9 protease inhibitors (PIs). PCA shows remarkable structure in RC across the different environments, which reveals differences in the patterns of resistance and cross-resistance between drugs or between drug classes. To probe the causes of the observed patterns, we develop a model to generate simulated data and subject these simulated data to an equivalent analysis. By comparing the outcomes of PCA on the original and the simulated data, we quantify which part of the total variance of the original data is due to non-specific effects, class-specific effects, and drug-specific effects of resistance mutations. We find that relative fitness is mainly drug-independent and that drug-specific effects are substantially bigger than class-specific effects for NRTIs, but not for NNRTIs or PIs. The observed patterns remain remarkably stable over the period of observation. Comparison with known potent combination therapies suggests that PCA helps to identify combinations that act synergistically in preventing the emergence of resistance.

Characterization of human immunodeficiency virus type 1 populations containing CXCR4-using variants from recently infected individuals

We screened 150 individuals from two recent seroconverter cohorts and found that six (4%) had CXCR4-using viruses. Clonal analysis of these six individuals, along with a seventh individual identified during clinical care as a recent seroconverter, revealed the presence of both X4- and dual-tropic variants in these recently infected adults. The ability of individual CXCR4-using variants to infect cells expressing CD4/CXCR4 or CD4/CCR5 varied dramatically. These data demonstrate that virus populations in some newly infected individuals can consist of either heterogeneous populations containing both CXCR4-using and CCR5-tropic viruses, or homogeneous populations containing only CXCR4-using viruses. The presence of CXCR4-using viruses at early stages of infection suggests that testing for viral tropism before using CCR5 antagonists may be important even in persons with known recent infection. The presence of CXCR4-using viruses in a subset of newly infected individuals could impact the efficacies of vaccine and microbicide strategies that target CCR5-tropic viruses.

HIV-1 tropism and survival in vertically infected Ugandan infants

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) may utilize the CXCR4 coreceptor (X4 virus), the CCR5 coreceptor (R5 virus), or both (dual/mixed [DM] virus). We analyzed HIV-1 coreceptor tropism in Ugandan infants enrolled in the HIVNET (HIV Network for Prevention Trials) 012 trial.

METHODS

Plasma or serum was analyzed using a commercial coreceptor tropism assay. HIV env subtype was determined by phylogenetic methods.

RESULTS

Tropism results were obtained for 57 samples from infants collected 6-14 weeks after birth. Fifty-two infants had only R5 virus, and 5 had either X4 or DM virus. The mothers of those 5 infants also had X4 or DM virus. In infants, subtype D infection was associated with high-level infectivity in CCR5-bearing cells and also with the detection of X4 or DM strains. High-level infectivity in CCR5-bearing cells was associated with decreased infant survival, but infection with X4 or DM virus was not. HIV clones from infants with DM viral populations showed different patterns of coreceptor use. V3 loop sequence-based algorithms predicted the tropism of some, but not all, env clones.

CONCLUSIONS

Complex patterns of HIV tropism were found in HIV-infected newborn infants. Subtype D infection was associated with X4 virus and with high-level replication in CCR5-bearing cells. High-level replication of R5 virus was associated with decreased infant survival.

Coreceptor tropism in human immunodeficiency virus type 1 subtype D: high prevalence of CXCR4 tropism and heterogeneous composition of viral populations

In human immunodeficiency virus type 1 (HIV-1) subtype B, CXCR4 coreceptor use ranges from approximately 20% in early infection to approximately 50% in advanced disease. Coreceptor use by non-subtype B HIV is less well characterized. We studied coreceptor tropism of subtype A and D HIV-1 collected from 68 pregnant, antiretroviral drug-naive Ugandan women (HIVNET 012 trial). None of 33 subtype A or 10 A/D-recombinant viruses used the CXCR4 coreceptor. In contrast, nine (36%) of 25 subtype D viruses used both CXCR4 and CCR5 coreceptors. Clonal analyses of the nine subtype D samples with dual or mixed tropism revealed heterogeneous viral populations comprised of X4-, R5-, and dual-tropic HIV-1 variants. In five of the six samples with dual-tropic strains, V3 loop sequences of dual-tropic clones were identical to those of cocirculating R5-tropic clones, indicating the presence of CXCR4 tropism determinants outside of the V3 loop. These dual-tropic variants with R5-tropic-like V3 loops, which we designated "dual-R," use CCR5 much more efficiently than CXCR4, in contrast to dual-tropic clones with X4-tropic-like V3 loops ("dual-X"). These observations have implications for pathogenesis and treatment of subtype D-infected individuals, for the association between V3 sequence and coreceptor tropism phenotype, and for understanding potential mechanisms of evolution from exclusive CCR5 use to efficient CXCR4 use by subtype D HIV-1.