Distinct genomic landscapes of gastroesophageal adenocarcinoma depending on PD-L1 expression identify mutations in RAS-MAPK pathway and TP53 as potential predictors of immunotherapy efficacy

BACKGROUND

The impact of molecular alterations on programmed death-ligand 1 (PD-L1) combined positive score (CPS) is not well studied in gastroesophageal adenocarcinomas (GEAs). We aimed to characterize genomic features of tumors with different CPSs in GEAs.

PATIENTS AND METHODS

Genomic alterations of 2518 GEAs were compared in three groups (PD-L1 CPS ≥ 10, high; CPS = 1-9, intermediate; CPS < 1, low) using next-generation sequencing. We assessed the impact of gene mutations on the efficacy of immune checkpoint inhibitors (ICIs) and tumor immune environment based on the Memorial Sloan Kettering Cancer Center and The Cancer Genome Atlas databases.

RESULTS

High, intermediate, and low CPSs were seen in 18%, 54% and 28% of GEAs, respectively. PD-L1 positivity was less prevalent in women and in tissues derived from metastatic sites. PD-L1 CPS was positively associated with mismatch repair deficiency/microsatellite instability-high, but independent of tumor mutation burden distribution. Tumors with mutations in KRAS, TP53, and RAS-mitogen-activated protein kinase (MAPK) pathway were associated with higher PD-L1 CPSs in the mismatch repair proficiency and microsatellite stability (pMMR&MSS) subgroup. Patients with RAS-MAPK pathway alterations had longer overall survival (OS) from ICIs compared to wildtype (WT) patients [27 versus 13 months, hazard ratio (HR) = 0.36, 95% confidence interval (CI): 0.19-0.7, P = 0.016] and a similar trend was observed in the MSS subgroup (P = 0.11). In contrast, patients with TP53 mutations had worse OS from ICIs compared to TP53-WT patients in the MSS subgroup (5 versus 21 months, HR = 2.39, 95% CI: 1.24-4.61, P = 0.016).

CONCLUSIONS

This is the largest study to investigate the distinct genomic landscapes of GEAs with different PD-L1 CPSs. Our data may provide novel insights for patient selection using mutations in TP53 and RAS-MAPK pathway and for the development of rational combination immunotherapies in GEAs.

Abstract P5-08-03: Poly-ligand profiling and target identification from formalin-fixed-paraffin embedded HER2+ breast cancer specimens

We have previously described the ADAPT Biotargeting System™as a novel platform for highly multiplexed poly-ligand profiling of complex phenotypes such as drug response. Here we report extended capabilities of the this platform for target identification directly from formalin-fixed-paraffin embedded (FFPE) tissues using aptamer libraries enriched toward HER2+ breast cancer. Standard mass spectrometry-based biomarker and drug target discovery from FFPE tissues can be challenging due to limited amounts of tissue, harsh conditions of fixation and extraction and the general problem of masking by highly abundant proteins. A single stranded-oligodeoxynucleotide aptamer library was enriched on HER2+ FFPE breast cancer specimens and conjugated with biotin as well as a label transfer reagent, Sulfo-NHS-SS-Diazirine (Sulfo-SDAD). The biotinylated-SDAD conjugated library (B-SDAD-EL) was applied to HER2+ FFPE tissues and photocrosslinked to cognate binding partners within the FFPE sample in order to preserve aptamer-protein interactions under harsh denaturing conditions required for protein extraction and sample preparation. Aptamer-protein complexes were affinity purified and the label was transferred from bound aptamers to their binding partners under reducing conditions that enable proteomic digestion and high resolution mass spectrometry detection. An open database search was performed where the precursor ion tolerance was set to ± 500 Da for database searching, which enabled identification of peptides containing the transferred label as well as additional unknown variable modifications induced by the tissue fixation process. We identified proteins with known roles in HER2+ breast cancer along with several potentially drugable targets not previously associated with HER2 positivity. Differential expression of candidate targets was orthogonally confirmed by immunohistochemistry. By nature of its extreme molecular complexity and its ability to be enriched or “trained,” toward phenotypes of interest, the ADAPT Biotargeting SystemTM can be deployed to advance precision medicine by identifying predictive biomarkers and drug targets with novel associations to complex interactomes.

Citation Format: O'Neill HA, Tinder TT, Maher V, Rosenow M, Richards M, Santhanam R, Wei X, Domenyuk V, Miglarese MR, Spetzler D. Poly-ligand profiling and target identification from formalin-fixed-paraffin embedded HER2+ breast cancer specimens [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-08-03.

Abstract P2-09-09: Polyligand profiling differentiates cancer patients according to their benefit of treatment

Introduction: Deconvolution of multi-nodal perturbations in cancer network architecture demands highly multiplexed profiling assays. We demonstrate the value of polyligand profiling of tumor systems states using libraries of single stranded oligodeoxynucleotides (ssODN) to distinguish between tumor tissue from breast cancer patients who did or did not derive benefit from treatment regimens containing trastuzumab.

Methods: This study included cases from women with invasive breast cancer who received chemotherapy+ trastuzumab (C+T) or trastuzumab monotherapy with available retrospective data on the time to next treatment (TTNT). A library of 2x1012 unique ssODN was exposed to FFPE tissues from patients who benefited (B) or not (NB) from trastuzumab-based regimens in several rounds of positive and negative selection. Two enriched libraries were screened on independent set of 42 B and 19 NB cases using a modified IHC protocol for detection of bound ssODNs. Poly-Ligand Profiles (PLP) were scored by a blinded pathologist. Two libraries, EL-NB and EL-B, showed significant p-values between groups of responders and non-responders. A Cox-PH model was fitted using either tumors' HER2 status or PLP test results as the independent variable. Median survival time was calculated from the Kaplan-Meier estimate. A separate group of 63 cases with TTNT data from chemotherapy without trastuzumab was used as a control to distinguish prognostic from predictive performance.

Results: The PLP scores of EL-NB and EL-B were assessed by receiver operating characteristic (ROC) curves and resulted in a combined AUC value of 0.81. EL-NB and EL-B were able to effectively classify B and NB patients with either HER2-negative/equivocal (AUC = 0.73) or HER2-positive cancers (AUC = 0.84). In contrast, HER2 status alone yielded an AUC value of 0.47. The combined PLP scores for the independent set of 63 patients treated with C excluding trastuzumab resulted in an AUC value of 0.53, indicating that the assay was predictive and not simply prognostic. Kaplan-Meier curves analysis shows that PLP+ cases have 429 days median TTNT, while PLP- cases have 129 days (HR = 0.38, log-rank p = 0.001). Analysis based on HER2 status showed no significant difference in TTNT between patients that were HER2+ (280 days) or HER2-negative/equivocal (336 days, HR = 1.27, log-rank p =0.45).

Summary: Performance of the PLP assay in differentiating patients who did or did not benefit from trastuzumab therapy outperforms the standard IHC assay for HER2 status. These results represent a promising step towards the development of a CDx to identify the 50-70% of HER2+ patients who will not benefit from trastuzumab. In addition, PLP also has the potential to identify the HER2-negative/equivocal patients who may benefit from trastuzumab-containing regimens.

Citation Format: Domenyuk V, Gatalica Z, Santhanam R, Wei X, Stark A, Kennedy P, Toussaint B, Levenberg S, Wang R, Xiao N, Greil R, Rinnerthaler G, Gampenrieder S, Heimberger AB, Berry DJ, Barker A, Demetri GD, Quackenbush J, Marshall JL, Poste G, Vacirca JL, Vidal GA, Schwartzberg LS, Halbert DD, Voss A, Miglarese MR, Famulok M, Mayer G, Spetzler D. Polyligand profiling differentiates cancer patients according to their benefit of treatment [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-09-09.

Abstract P4-12-08: Use of an aptamer library based next generation omics platform for the development of a novel trastuzumab predictive assay

Introduction: Previous attempts to use individual aptamers as diagnostic reagents have failed to consistently achieve performance comparable to antibodies. Here we report a novel systems biology approach using poly-ligand aptamer libraries to identify responders and non-responders to traztuzumab-based regimens in metastatic breast cancer.

Methods: To overcome the fundamental limitation of the individual aptamer binding affinities, large libraries (106 species) were created so that potentially thousands of aptamers could bind to each of a multitude of targets related to the whole cellular changes in response to trastuzumab therapy. A set of breast cancer patients, which received trastuzumab mono- or combined therapy for at least 7 months were classified as “Responders” (R); cases with particular regimen discontinued in the period not exceeding 5 months were classified as “Non-Responders”(NR). A library of 2x1012 unique 90-mer ssDNA oligodeoxynucleotides (ssODN) was trained on FFPE tissue of both R and NR patients. Partitioning of aptamer libraries was done by microdissection of the tumor tissue, after incubation of aptamer library with the entire tissue section, to drive selection pressure toward cancer cells. A total of 10 cases of R and NR, 6 Her2+ cases each, were used to train separate aptamer libraries, with 1 positive and 2 counter selection cases per enrichment. Enriched libraries were screened on 20 R and 20 NR cases (11 Her2+ cases each) by adopting modified immunohistochemistry protocol. Each library was used as an independent reagent (similar to an antibody in IHC) across all 40 cases to evaluate the efficacy of the aptamer library to distinguish differences between the R and NR groups. Staining (DAB chromogen) profiles were scored from 0 to 3+ (nuclear and cytoplasmic staining) by a pathologist without any knowledge of the clinical outcomes. Initial validation was done by t-test using raw histological scores. Four libraries showed significant p-values between groups of responders and non-responders, a classification algorithm was constructed and evaluated using area under the receiver-operator characteristic curve (AUC). The datasets of two best-performing libraries were combined into one model using logistic regression to further improved the classifier performance.

Results: Of seventeen trained libraries, eight were evaluated and four showed significant correlation to clinical benefit with a minimum accuracy of 75% for each library when evaluated independently. Furthermore, two libraries showed exceptional performance (ROC curve AUC of 0.86 and 0.77). Combination of the profiling data from these two libraries using logistic regression resulted in an AUC of 0.985. A prospective validation of aptamer histochemical theranostic testing has been initiated.

Summary: Enriched aptamer libraries appear to distinguish trastuzumab responsiveness in metastatic breast cancer. This technology could be used as an additional technique beyond FISH testing to determine sensitivity to anti-HER2 agents. The demonstrated platform is applicable to virtually any disease where the safe and effective use of corresponding drug is yet to be improved.

Citation Format: Spetzler D, Domenyuk V, Santhanam R, Wei X, Stark A, Wang J, Gatalica Z, Miglarese M, Vidal G, Schwartzberg LS. Use of an aptamer library based next generation omics platform for the development of a novel trastuzumab predictive assay [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-12-08.

Abstract P2-01-08: Adaptive dynamic artificial poly-ligand targeting: Aptamer-based profiling of liquid biopsies to improve the accuracy of breast cancer diagnoses in women with dense breast tissue

Introduction:

Breast cancer screening relies upon mammography, but for women with dense breast tissue this method is often uninformative. Routine screening identifies suspicious breast lesions in some women, but the pain and risk associated with follow-up biopsies along with the poor accuracy of traditional histopathology urgently call for improved approaches to breast cancer screening. This is especially important for those high-risk patients for whom mammography is of limited value. We describe a non-invasive liquid biopsy method of profiling plasma exosome preps designed to improve the accuracy and safety of breast cancer screening for women with dense breast tissue.

Results:

We incubated plasma samples (300 microliters per sample) from breast cancer patients (n=60) and a control cohort (n=60) with a high-complexity DNA aptamer library using a modified SELEX scheme, termed “adaptive dynamic artificial poly-ligand targeting (ADAPTTM)”. Differentially bound (cancer vs. non-cancer) aptamers were recovered from precipitated exosomes and were identified by deep sequencing. Two thousand aptamer sequences were resynthesized and used to probe a larger set of 500 plasma samples from a patient cohort (n=206) and a control cohort comprised of self-reported healthy volunteers (n=117) and patients whose biopsies led to a diagnosis of non-cancer (n=177). We employed several statistical models to build a cancer/non-cancer predictor, including a Random Generalized Linear Model (RGLM) and a Random Forest Model (RFM). Both models yielded an equivalent classification performance with areas under the receiver-operator characteristic curve (ROC AUC) of 0.7. Testing the prediction performance by 100 Out-of-Bag permutations or by pre-filtered (read cutoff and estimated sample size) cross-validation (CV) resulted in ROC AUC values of 0.66 and 0.62, respectively. When samples were randomly assigned to groups, the aptamers were no longer able to distinguish the groups (ROC AUC = 0.54), indicating that the underlying information driving the model is truly specific to cancer. Importantly, incorporation of BIRAD results as a clinical covariate did not influence model performance, signifying that predictions by ADAPTTM were independent of breast tissue density.

Conclusions:

We have identified a set of 2000 DNA aptamers that distinguish women with breast cancer from women without breast cancer. Our liquid biopsy approach requires only 300 microliters of plasma and is amenable to high-throughput processing. By employing a number of statistical approaches including rigorous cross-validation, we consistently achieve cross validation ROC AUC values approaching 0.7. The performance of the predictor was not affected by BIRAD scores, supporting its potential utility in difficult cases where imaging is insufficient, such as in women with dense breast tissue. Further optimization of the aptamer library and testing on additional samples should improve performance. Upon complete validation, an ADAPTTM – derived breast cancer test may serve as a vital diagnostic adjunct that can be easily incorporated into standard clinical practice.

Citation Format: Domenyuk V, Zhong Z, Wang J, Stark A, Chen W, Xiao N, Miglarese MR, Famulok M, Mayer G, Spetzler DB. Adaptive dynamic artificial poly-ligand targeting: Aptamer-based profiling of liquid biopsies to improve the accuracy of breast cancer diagnoses in women with dense breast tissue. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-01-08.

A circulating microvesicle-based biosignature for the detection of colorectal cancer

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Background: Microvesicles are principally derived either from the endosomal pathway (as exosomes) or shed directly from the plasma membrane. They are between 40-500 nm in diameter and are secreted by most cell types, including tumor cells. In circulation, microvesicles appear to participate in cellular communication by transporting mRNAs, miRs and proteins from their cell of origin to target cells where they can elicit biological responses. The quantity and protein topography of microvesicles shed from cancer cells varies considerably compared to those shed from normal cells. Thus, the concentration of circulating plasma microvesicles with molecular markers indicative of the disease state can be used as a robust and informative blood-based biosignature. In this study we report the results of the application of a novel multiplexed method for quantifying and profiling microvesicles in plasma for the detection of colorectal cancer.

Methods: We have developed a versatile mulitplexed microvesicle-based discovery panel with 73 different antibodies that target surface proteins of various microvesicle subpopulations. This system was used to develop a microvesicle-derived biosignature composed of 2 different surface membrane protein biomarkers.

Results: In this study, we demonstrate that a combination of TMEM211 and CD24 provide a robust signature for the detection of colorectal cancer (CRC). We isolated microvesicles from plasma of 257 patients with CRC, 57 stage I, 104 stage II, 80 stage 3, 6 stage IV, and 11 of unknown stage; 327 self-described, age-range matched normal plasma specimens were used for the control population. The level of TMEM211 and CD24 containing microvesicles for these samples was determined using a multiplexed immunoassay. Thresholds were empirically determined to maximize the sensitivity and specificity of CRC detection, resulting in a sensitivity of 90% with a specificity of 85% with an AUC of .91.

Conclusions: This study demonstrates that it is possible to use circulating microvesicles for the development of a highly sensitive and specific blood-based assay to detect CRC.

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Recent developments of bio-molecular motors as on-chip devices using single molecule techniques

The integration of microfluidic devices with single molecule motor detection techniques allows chip based devices to reach sensitivity levels previously unattainable.