Automated subcellular localization and quantification of protein expression in tissue microarrays

Quantitative Measurement of HER2 Expression in Non-Small Cell Lung Cancer With a High-Sensitivity Assay

Recently, low human epidermal growth factor receptor 2 (HER2) protein expression has been proposed as a predictive biomarker for response to the antibody-drug conjugate trastuzumab deruxtecan (T-DXd) in metastatic breast cancer. HER2 expression in non-small cell lung cancer (NSCLC) patients has never been carefully measured, and little is known about the frequency of cases with unamplified but detectable levels of the protein. Although some HER2-targeted therapies have been studied in NSCLC patients, they have been restricted to those with genomic ERBB2 gene alterations, which only represent relatively rare cases of NSCLC. Still, emerging investigations of T-DXd in NSCLC have shown promise in patients with unamplified HER2. Taken together, we hypothesize that there may be many cases of NSCLC with levels of HER2 protein expression comparable with levels seen in breast cancer that benefit from T-DXd. Here, we used a previously validated, analytic, quantitative immunofluorescence (QIF) assay that is more sensitive than legacy clinical HER2 immunohistochemistry assays. We measured HER2 protein levels in NSCLC cases to determine the proportion of cases with detectable HER2 expression. Using cell line calibration microarrays alongside our QIF method enabled us to convert HER2 signal into units of attomoles per mm2. We found that over 63% of the 741 analyzed NSCLC cases exhibited HER2 expression above the limit of detection, with more than 17% of them exceeding the lower limit of quantification. Although the threshold for response to T-DXd in breast cancer is still unknown, many cases of NSCLC have expression in a range comparable to breast cancer cases with immunohistochemistry scores of 1+ or 2+. Our assay could potentially select NSCLC cases with a detectable target (ie, HER2) that might benefit from HER2 antibody-drug conjugates, irrespective of ERBB2 genomic alterations.

BCAM (basal cell adhesion molecule) protein expression in different tumor populations

Basal Cell Adhesion Molecule (BCAM), a receptor for laminin subunit α5, plays a crucial role in the pathogenesis of various malignancies. Notably, evidence of hypermethylation at multiple immune checkpoints in patients with low BCAM expression suggests these individuals may respond favorably to immunotherapy using ICIs (immune checkpoint inhibitors). This finding lays the foundation for the hypothesis that BCAM may serve as an important biomarker in cancer patients. To investigate this potential, we evaluated BCAM expression patterns in 3114 patients from both discovery and validation cohorts, spanning seven cancer types, using quantitative immunofluorescence (QIF). We also explored the correlation between BCAM and PD-L1 expressions within these cohorts, aiming to establish its potential predictive value for immunotherapy response. Our findings indicate that BCAM was highly expressed in ovarian (79.2%) and lung (78.5%) tumors, with lower yet significant expression in breast (37.7%), head and neck (31.3%), and bladder-urothelial tumors (27.6%). Notably, high BCAM expression was associated with better OS in NSCLC. More importantly, BCAM expression did not correlate with PD-L1 protein expression in any of these tumors, highlighting its independent predictive potential. The widespread expression of BCAM across multiple tumor types, coupled with its lack of correlation with PD-L1 expression, highlights its potential as a predictive novel biomarker across various cancer types.

TIGIT expression in renal cell carcinoma infiltrating T cells is variable and inversely correlated with PD-1 and LAG3

PURPOSE

Immune checkpoint inhibitors have revolutionized the treatment of renal cell carcinoma (RCC), but many patients do not respond to therapy and the majority develop resistant disease over time. Thus, there is increasing need for alternative immunomodulating agents. The co-inhibitory molecule T-cell immunoglobulin and ITIM domain (TIGIT) may play a role in resistance to approved immune checkpoint inhibitors and is being investigated as a potential therapeutic target. The purpose of this study was to quantify TIGIT positivity in tumor-infiltrating T cells in RCC.

METHODS

We employed tissue microarrays containing specimens from primary RCC tumors, adjacent normal renal tissue, and RCC metastases to quantify TIGIT within tumor-infiltrating CD3+ T cells using quantitative immunofluorescent analysis. We also compared these results to TIGIT+ CD3+ levels in four other tumor types (melanoma, non-small cell lung, cervical, and head and neck cancers).

RESULTS

We did not observe significant differences in TIGIT positivity between primary RCC tumors and patient-matched metastatic samples. We found that the degree of TIGIT positivity in RCC is comparable to that in lung cancer but lower than that in melanoma, cervical, and head and neck cancers. Correlation analysis comparing TIGIT positivity to previously published, patient-matched spatial proteomic data by our group revealed a negative association between TIGIT and the checkpoint proteins PD-1 and LAG3.

CONCLUSION

Our findings support careful evaluation of TIGIT expression on T cells in primary or metastatic RCC specimens for patients who may be treated with TIGIT-targeting antibodies, as increased TIGIT positivity might be associated with a greater likelihood of response to therapy.

GP100 expression is variable in intensity in melanoma

Drugs or cellular products that bind to gp100 are being investigated for treatment of cutaneous melanoma. The relative specificity of gp100 expression in melanocytes makes it an attractive target to harness for therapeutic intent. For example, Tebentafusp, a bispecific gp100 peptide-HLA-directed CD3 T cell engager, has generated significant enthusiasm in recent years due to its success in improving outcomes for uveal melanoma and is being studied in cutaneous melanoma. However, the extent and intensity of gp100 expression in advanced cutaneous melanoma has not been well studied. Here, we interrogated a large cohort of primary and metastatic melanomas for gp100 expression by immunohistochemistry. Expression in metastatic samples was globally higher and almost uniformly positive, however the degree of intensity was variable. Using a quantitative immunofluorescence method, we confirmed the variability in expression. As gp100-binding drugs are assessed in clinical trials, the association between activity of the drugs and the level of gp100 expression should be studied in order to potentially improve patient selection.

Melanocortin-1 Receptor Expression as a Marker of Progression in Melanoma

PURPOSE

Melanocortin-1 receptor (MC1R) plays a critical role in human pigmentation and DNA repair mechanisms. MC1R-targeting agents are being investigated in clinical trials in patients with melanoma, yet large studies investigating the rate and degree of MC1R expression in primary and metastatic human melanoma tissue are lacking.

METHODS

Using tissue microarrays containing three large cohorts of 225 cases of benign nevi, 189 with primary melanoma, and 271 with metastatic melanoma, we applied quantitative immunofluorescence and immunohistochemistry to comprehensively study MC1R protein expression.

RESULTS

We show a stepwise elevation of MC1R expression in different stages of melanoma progression (nevi, primary, metastasis). Higher MC1R expression was seen in deeper (>1 mm) primary lesions and ulcerated lesions and was associated with shorter survival in primary and metastatic tumors. On multivariable analysis, Breslow thickness, male sex, and chronic sun exposure were independent predictors of worse overall survival in the primary melanoma cohort.

CONCLUSION

Our data suggest that MC1R might be a valuable drug target in aggressive melanoma. Additional studies are warranted to determine its functional significance in melanoma progression and its utility as a predictive biomarker in patients receiving MC1R-directed therapies.

High-Plex Assessment of Biomarkers in Tumors

The assessment of biomarkers plays a critical role in the diagnosis and treatment of many cancers. Biomarkers not only provide diagnostic, prognostic, or predictive information but also can act as effective targets for new pharmaceutical therapies. As the utility of biomarkers increases, it becomes more important to utilize accurate and efficient methods for biomarker discovery and, ultimately, clinical assessment. High-plex imaging studies, defined here as assessment of 8 or more biomarkers on a single slide, have become the method of choice for biomarker discovery and assessment of biomarker spatial context. In this review, we discuss methods of measuring biomarkers in slide-mounted tissue samples, detail the various high-plex methods that allow for the simultaneous assessment of multiple biomarkers in situ, and describe the impact of high-plex biomarker assessment on the future of anatomic pathology.

Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images

Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB), resulting in a brown coloration, whereas hematoxylin serves as a blue counterstain for cell nuclei. The protein expression level is quantified through the H-score, calculated from DAB staining intensity within the target cell region. Traditionally, this process requires evaluation by 2 expert pathologists, which is both time consuming and subjective. To enhance the efficiency and accuracy of this process, we have developed an automatic algorithm for quantifying the H-score of IHC images. To characterize protein expression in specific cell regions, a deep learning model for region recognition was trained based on hematoxylin staining only, achieving pixel accuracy for each class ranging from 0.92 to 0.99. Within the desired area, the algorithm categorizes DAB intensity of each pixel as negative, weak, moderate, or strong staining and calculates the final H-score based on the percentage of each intensity category. Overall, this algorithm takes an IHC image as input and directly outputs the H-score within a few seconds, significantly enhancing the speed of IHC image analysis. This automated tool provides H-score quantification with precision and consistency comparable to experienced pathologists but at a significantly reduced cost during IHC diagnostic workups. It holds significant potential to advance biomedical research reliant on IHC staining for protein expression quantification.

Spatial and temporal heterogeneity of tumor immune microenvironment between primary tumor and brain metastases in NSCLC

BACKGROUND

Brain metastasis is a common outcome in non-small cell lung cancer, and despite aggressive treatment, its clinical outcome is still frustrating. In recent years, immunotherapy has been developing rapidly, however, its therapeutic outcomes for primary lung cancer and brain metastases are not the same, suggesting that there may be differences in the immune microenvironment of primary lung cancer and brain metastases, however, we currently know little about these differences.

METHODS

Seventeen paired samples of NSCLC and their brain metastases and 45 other unpaired brain metastases samples were collected for the current study. Immunohistochemical staining was performed on all samples for the following markers: immune checkpoints CTLA-4, PD-1, PD-L1, B7-H3, B7-H4, IDO1, and EphA2; tumor-infiltrating lymphocytes (TILs) CD3, CD4, CD8, and CD20; tumor-associated microglia/macrophages (TAMs) CD68 and CD163; and tumor proliferation index Ki-67. The differences in expression of these markers were compared in 17 paired samples, and the effect of the expression level of these markers on the prognosis of patients was analyzed in lung adenocarcinoma brain metastases samples. Subsequently, multiplex immunofluorescence staining was performed in a typical lung-brain paired sample based on the aforementioned results. The multiplex immunofluorescence staining results revealed the difference in tumor immune microenvironment between primary NSCLC and brain metastases.

RESULTS

In 17 paired lesions, the infiltration of CTLA-4+ (P = 0.461), PD-1+ (P = 0.106), CD3+ (P = 0.045), CD4+ (P = 0.037), CD8+ (P = 0.008), and CD20+ (P = 0.029) TILs in brain metastases were significantly decreased compared with primary tumors. No statistically significant difference was observed in the CD68 (P = 0.954) and CD163 (P = 0.654) TAM infiltration between primary NSCLC and paired brain metastases. In all the brain metastases lesions, the expression of PD-L1 is related to the time interval of brain metastases in NSCLC. In addition, the Cox proportional hazards regression models showed high expression of B7-H4 (hazard ratio [HR] = 3.276, 95% confidence interval [CI] 1.335-8.041, P = 0.010) and CD68 TAM infiltration (HR = 3.775, 95% CI 1.419-10.044, P = 0.008) were independent prognosis factors for lung adenocarcinoma brain metastases patients.

CONCLUSIONS

Both temporal and spatial heterogeneity is present between the primary tumor and brain metastases of NCSLC. Brain metastases lesions exhibit a more immunosuppressive tumor immune microenvironment. B7-H4 and CD68+ TAMs may have potential therapeutic value for lung adenocarcinoma brain metastases patients.

HLA-DR expression in melanoma: from misleading therapeutic target to potential immunotherapy biomarker

Since the advent of anti-PD1 immune checkpoint inhibitor (ICI) immunotherapy, cutaneous melanoma has undergone a true revolution with prolonged survival, as available 5-year updates for progression-free survival and overall survival demonstrate a durable clinical benefit for melanoma patients receiving ICI. However, almost half of patients fail to respond to treatment, or relapse sooner or later after the initial response to therapy. Little is known about the reasons for these failures. The identification of biomarkers seems necessary to better understand this resistance. Among these biomarkers, HLA-DR, a component of MHC II and abnormally expressed in certain tumor types including melanoma for unknown reasons, seems to be an interesting marker. The aim of this review, prepared by an interdisciplinary group of experts, is to take stock of the current literature on the potential interest of HLA-DR expression in melanoma as a predictive biomarker of ICI outcome.

Immune Inhibitory Molecule PD-1 Homolog (VISTA) Colocalizes with CD11b Myeloid Cells in Melanoma and Is Associated with Poor Outcomes

Tumors evade immunity through the overexpression of immune inhibitory molecules in the tumor microenvironment such as PD-L1/B7-H1. An immune inhibitory molecule named PD-1 homolog (also known as V-domain Ig-containing suppressor of T cell activation [VISTA]) functions to control both T cells and myeloid cells. Current clinical trials using anti-VISTA-blocking agents for treatment of cancer are ongoing. We sought to determine the extent of VISTA expression in primary cutaneous melanomas (n = 190), identify the critical cell types expressing VISTA, and correlate its expression with PD-L1 expression using multiplexed quantitative immunofluorescence. Within the tumor subcompartments, VISTA is most highly expressed on CD11b myeloid cells, and PD-L1 is most highly expressed on CD68 myeloid cells in our melanoma cohort. There is little correlation between VISTA and PD-L1 expression intensity, suggesting that individual tumors have distinct immunosuppressive tumor microenvironments. High levels of VISTA expression on CD11b myeloid cells but not PD-L1 expression were associated with greater melanoma recurrence and greater all-cause mortality. Our findings suggest that cell-specific VISTA expression may be a negative prognostic biomarker for melanoma and a future potential therapeutic target.

Rapid responses of human pluripotent stem cells to cyclic mechanical strains applied to integrin by acoustic tweezing cytometry

Acoustic tweezing cytometry (ATC) is an ultrasound-based biophysical technique that has shown the capability to promote differentiation of human pluripotent stem cells (hPSCs). This study systematically examined how hPSCs respond to cyclic mechanical strains applied by ATC via displacement of integrin-bound microbubbles (averaged diameter of 4.3 µm) using ultrasound pulses (acoustic pressure 0.034 MPa, center frequency 1.24 MHz and pulse repetition frequency 1 Hz). Our data show downregulation of pluripotency marker Octamer-binding transcription factor 4 (OCT4) by at least 10% and increased nuclear localization of Yes-associated protein (YAP) by almost 100% in hPSCs immediately after ATC application for as short as 1 min and 5 min respectively. Analysis of the movements of integrin-anchored microbubbles under ATC stimulations reveals different stages of viscoelastic characteristic behavior and increasing deformation of the integrin-cytoskeleton (CSK) linkage. The peak displacement of integrin-bound microbubbles increased from 1.45 ± 0.16 to 4.74 ± 0.67 μm as the duty cycle of ultrasound pulses increased from 5% to 50% or the duration of each ultrasound pulse increased from 0.05 to 0.5 s. Real-time tracking of integrin-bound microbubbles during ATC application detects high correlation of microbubble displacements with OCT4 downregulation in hPSCs. Together, our data showing fast downregulation of OCT4 in hPSCs in respond to ATC stimulations highlight the unique mechanosensitivity of hPSCs to integrin-targeted cyclic force/strain dependent on the pulse duration or duty cycle of ultrasound pulses, providing insights into the mechanism of ATC-induced accelerated differentiation of hPSCs.

Digital spatial profiling of melanoma shows CD95 expression in immune cells is associated with resistance to immunotherapy

Although immune checkpoint inhibitor (ICI) therapy has dramatically improved outcome for metastatic melanoma patients, many patients do not benefit. Since adverse events may be severe, biomarkers for resistance would be valuable, especially in the adjuvant setting. We performed high-plex digital spatial profiling (DSP) using the NanoString GeoMx® on 53 pre-treatment specimens from ICI-treated metastatic melanoma cases. We interrogated 77 targets simultaneously in four molecular compartments defined by S100B for tumor, CD68 for macrophages, CD45 for leukocytes, and nonimmune stromal cells defined as regions negative for all three compartment markers but positive for SYTO 13. For DSP validation, we confirmed the results obtained for some immune markers, such as CD8, CD4, CD20, CD68, CD45, and PD-L1, by quantitative immunofluorescence (QIF). In the univariable analysis, 38 variables were associated with outcome, 14 of which remained significant after multivariable adjustment. Among them, CD95 was further validated using multiplex immunofluorescence in the Discovery immunotherapy (ITX) Cohort and an independent validation cohort with similar characteristics, showing an association between high levels of CD95 and shorter progression-free survival. We found that CD95 in stroma was associated with resistance to ICI. With further validation, this biomarker could have value to select patients that will not benefit from immunotherapy.

Development of an Enzyme-Linked Immunosorbent Assay (ELISA) for the Quantification of ARID1A in Tissue Lysates

ARID1A is a subunit of the mammalian SWI/SNF complex, which is thought to regulate gene expression through restructuring chromatin structures. Its gene ARID1A is frequently mutated and ARID1A levels are lowered in several human cancers, especially gynecologic ones. A functional ARID1A loss may have prognostic or predictive value in terms of therapeutic strategies but has not been proposed based on a quantitative method. Hardly any literature is available on ARID1A levels in tumor samples. We developed an indirect enzyme-linked immunosorbent assay (ELISA) for ARID1A based on the current EMA and FDA criteria. We demonstrated that our ELISA provides the objective, accurate, and precise quantification of ARID1A concentrations in recombinant protein solutions, cell culture standards, and tissue lysates of tumors. A standard curve analysis yielded a 'goodness of fit' of R2 = 0.99. Standards measured on several plates and days achieved an inter-assay accuracy of 90.26% and an inter-assay precision with a coefficient of variation of 4.53%. When tumor lysates were prepared and measured multiple times, our method had an inter-assay precision with a coefficient of variation of 11.78%. We believe that our suggested method ensures a high reproducibility and can be used for a high sample throughput to determine the ARID1A concentration in different tumor entities. The application of our ELISA on various tumor and control tissues will allow us to explore whether quantitative ARID1A measurements in tumor samples are of predictive value.

Phase II Window Study of Olaparib Alone or with Cisplatin or Durvalumab in Operable Head and Neck Cancer

Purpose

We conducted a phase II randomized noncomparative window of opportunity (WOO) trial to evaluate the inhibition of cellular proliferation and the modulation of immune microenvironment after treatment with olaparib alone or in combination with cisplatin or durvalumab in patients with operable head and neck squamous cell carcinoma (HNSCC).

Experimental Design

Forty-one patients with HNSCC were randomized to cisplatin plus olaparib (arm A), olaparib alone (arm B), no treatment (arm C) or durvalumab plus olaparib (arm D). The primary endpoint was to evaluate the percentage of patients in each arm that achieved a reduction of at least 25% in Ki67. Secondary endpoints included objective response rate (ORR), safety, and pathologic complete response (pCR) rate. Paired baseline and resection tumor biopsies and blood samples were evaluated for prespecified biomarkers.

Results

A decrease in Ki67 of at least 25% was observed in 44.8% of treated patients, as measured by quantitative immunofluorescence. The ORR among treated patients was 12.1%. pCR was observed in 2 patients. Two serious adverse events occurred in 2 patients.Programmed death ligand 1 (PD-L1) levels [combined positive score (CPS)] were significantly higher after treatment in arms A and D. Expression of CD163 and colony-stimulating factor 1 receptor (CSF1R) genes, markers of M2 macrophages, increased significantly posttreatment whereas the expression of CD80, a marker of M1 macrophages, decreased.

Conclusion

Preoperative olaparib with cisplatin or alone or with durvalumab was safe in the preoperative setting and led to decrease in Ki67 of at least 25% in 44.8% of treated patients. Olaparib-based treatment modulates the tumor microenvironment leading to upregulation of PD-L1 and induction of protumor features of macrophages.

Significance

HNSCC is characterized by defective DNA repair pathways and immunosuppressive tumor microenvironment. PARP inhibitors, which promote DNA damage and "reset" the inflammatory tumor microenvironment, can establish an effective antitumor response. This phase II WOO trial in HNSCC demonstrated the immunomodulatory effects of PARP inhibitor-induced DNA damage. In this chemo-naïve population, PARP inhibitor-based treatment, reduced tumor cell proliferation and modulated tumor microenvironment. After olaparib upregulation of PD-L1 and macrophages, suggests that combinatorial treatment might be beneficial.

Synopsis

Our WOO study demonstrates that preoperative olaparib results in a reduction in Ki67, upregulation of PD-L1 CPS, and induction of protumor features of macrophages in HNSCC.

Subsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma

PURPOSE

IFN signaling in the tumor microenvironment is a critical determinant of both response and resistance of cancer to immune checkpoint inhibitors (ICI). We hypothesized that distinct patterns of IFN signaling in melanoma are associated with clinical response or resistance to ICIs.

EXPERIMENTAL DESIGN

Two tissue microarrays containing samples from 97 patients with metastatic melanoma who received nivolumab, pembrolizumab, or a combination of ipilimumab and nivolumab at Yale New Haven Hospital between 2011 and 2017 were randomized into discovery and validation cohorts. Samples were stained and visualized using multiplexed immunofluorescence microscopy for STAT1, STAT1 phosphorylated at Y701 (pSTAT1Y701), and PD-L1, and signals were quantified using the automated quantitative analysis method of quantitative immunofluorescence. Treatment response was assessed using RECIST, and overall survival was analyzed. For in vitro studies, human melanoma cell lines were stimulated with IFNγ and IFNβ, and Western blotting was performed.

RESULTS

Pretreatment STAT1 levels were higher in responders to ICIs [complete response/partial response/stable disease (SD) for > 6 months] than in nonresponders (SD < 6 months/progressive disease). Higher pretreatment STAT1 levels were associated with improved survival after ICIs in both the discovery and validation cohorts. Western blot analysis of human melanoma cell lines stimulated with IFN demonstrated distinct patterns of upregulation of STAT1 compared with pSTAT1Y701 and PD-L1. When combining STAT1 and PD-L1 markers, patients with STAT1highPD-L1low tumors had improved survival compared with those with STAT1lowPD-L1high tumors.

CONCLUSIONS

STAT1 may better predict melanoma response to ICIs than current strategies, and combined STAT1 and PD-L1 biomarkers may provide insight into IFN-responsive versus IFN-resistant states.

Multiplex Immunohistochemistry and Immunofluorescence: A Practical Update for Pathologists

Our understanding of the biology and management of human disease has undergone a remarkable evolution in recent decades. Improved understanding of the roles of complex immune populations in the tumor microenvironment has advanced our knowledge of antitumor immunity, and immunotherapy has radically improved outcomes for many advanced cancers. Digital pathology has unlocked new possibilities for the assessment and discovery of the tumor microenvironment, such as quantitative and spatial image analysis. Despite these advances, tissue-based evaluations for diagnosis and prognosis continue to rely on traditional practices, such as hematoxylin and eosin staining, supplemented by the assessment of single biomarkers largely using chromogenic immunohistochemistry (IHC). Such approaches are poorly suited to complex quantitative analyses and the simultaneous evaluation of multiple biomarkers. Thus, multiplex staining techniques have significant potential to improve diagnostic practice and immuno-oncology research. The different approaches to achieve multiplexed IHC and immunofluorescence are described in this study. Alternatives to multiplex immunofluorescence/IHC include epitope-based tissue mass spectrometry and digital spatial profiling (DSP), which require specialized platforms not available to most clinical laboratories. Virtual multiplexing, which involves digitally coregistering singleplex IHC stains performed on serial sections, is another alternative to multiplex staining. Regardless of the approach, analysis of multiplexed stains sequentially or simultaneously will benefit from standardized protocols and digital pathology workflows. Although this is a complex and rapidly advancing field, multiplex staining is now technically feasible for most clinical laboratories and may soon be leveraged for routine diagnostic use. This review provides an update on the current state of the art for tissue multiplexing, including the capabilities and limitations of different techniques, with an emphasis on potential relevance to clinical diagnostic practice.

Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer

The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL's advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Quantitative, Spatially Defined Expression of Leukocyte-associated Immunoglobulin-like Receptor in Non-small Cell Lung Cancer

Targeting the interaction of leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) and its ligands has been shown to reinstate antitumor immunity. In addition, the introduction of the LAIR-1 decoy protein, LAIR-2, sensitizes previously resistant lung tumors to programmed death-1 (PD-1) blockade, indicating the potential of LAIR-1 as an alternative marker for anti-PD-1 resistance in lung cancer. Here, we assessed LAIR-1 as compared with programmed death-ligand 1 (PD-L1) expression in various tumors, with a focus on non-small cell lung cancer (NSCLC) and its histologic subtypes using multiplexed quantitative immunofluorescence (mQIF) in 287 (discovery cohort) and 144 (validation cohort) patients with NSCLC. In addition, using multispectral imaging technology on mQIF images, we evaluated the localization of LAIR-1 on various cell types. We observed that CD14+, CD68+, and CD163+ monocytes and CK+ tumor cells predominantly expressed LAIR-1 more than other cell types. Furthermore, LAIR-1 expression in the tumor compartment was significantly higher in patients with lung adenocarcinoma (LUAD) than those with lung squamous cell carcinoma subtype (**, P = 0.003). Our results indicated that high tumor LAIR-1 expression in patients with LUAD is negatively associated with OS (overall survival, HR = 2.4; *, P = 0.02) highlighting its prognostic value in LUAD but not in other subtypes. The Pearson correlation between LAIR-1 and PD-L1 is 0.31; however, mutual exclusive staining pattern (i.e., several cases were positive for LAIR-1 and negative for PD-L1) was observed. Altogether, our data suggest that the combination therapy of anti-PD-1/PD-L1 with anti-LAIR-1 or the anti-LAIR-1 monotherapy alone may be promising cancer immunotherapeutic strategies.

Significance

The spatial, quantitative assessment of LAIR-1 in NSCLC shows positive association of OS with high LAIR-1+/CD68+ cell densities and negative association of OS with high LAIR-1 expression in LUAD tumor subtype.

Reliability of CD44, CD24, and ALDH1A1 immunohistochemical staining: Pathologist assessment compared to quantitative image analysis

Background

The data on the expression of stem cell markers CD44, CD24, and ALDH1A1 in the breast tissue of cancer-free women is very limited and no previous studies have explored the agreement between pathologist and computational assessments of these markers. We compared the immunohistochemical (IHC) expression assessment for CD44, CD24, and ALDH1A1 by an expert pathologist with the automated image analysis results and assessed the homogeneity of the markers across multiple cores pertaining to each woman.

Methods

We included 81 cancer-free women (399 cores) with biopsy-confirmed benign breast disease in the Nurses' Health Study (NHS) and NHSII cohorts. IHC was conducted with commercial antibodies [CD44 (Dako, Santa Clara, CA, USA) 1:25 dilution; CD24 (Invitrogen, Waltham, MA, USA) 1:200 dilution and ALDH1A1 (Abcam, Cambridge, United Kingdom) 1:300 dilution]. For each core, the percent positivity was quantified by the pathologist and Definiens Tissue Studio. Correlations between pathologist and computational scores were evaluated with Spearman correlation (for categorical positivity: 0, >0-<1, 1-10, >10-50, and >50%) and sensitivity/specificity (for binary positivity defined with 1 and 10% cut-offs), using the pathologist scores as the gold standard. Expression homogeneity was examined with intra-class correlation (ICC). Analyses were stratified by core [normal terminal duct-lobular units (TDLUs), benign lesions] and tissue type (epithelium, stroma).

Results

Spearman correlation between pathologist and Definiens ranged between 0.40-0.64 for stroma and 0.66-0.68 for epithelium in normal TDLUs cores and between 0.24-0.60 for stroma and 0.61-0.64 for epithelium in benign lesions. For stroma, sensitivity and specificity ranged between 0.92-0.95 and 0.24-0.60, respectively, with 1% cut-off and between 0.43-0.88 and 0.73-0.85, respectively, with 10% cut-off. For epithelium, 10% cut-off resulted in better estimates for both sensitivity and specificity. ICC between the cores was strongest for CD44 for both stroma and epithelium in normal TDLUs cores and benign lesions (range 0.74-0.80). ICC for CD24 and ALDH1A ranged between 0.42-0.63 and 0.44-0.55, respectively.

Conclusion

Our findings show that computational assessments for CD44, CD24, and ALDH1A1 exhibit variable correlations with manual assessment. These findings support the use of computational platforms for IHC evaluation of stem cell markers in large-scale epidemiologic studies. Pilot studies maybe also needed to determine appropriate cut-offs for defining staining positivity.

Analysis of MRE11 and Mortality Among Adults With Muscle-Invasive Bladder Cancer Managed With Trimodality Therapy

IMPORTANCE

Bladder-preserving trimodality therapy can be an effective alternative to radical cystectomy for treatment of muscle-invasive bladder cancer (MIBC), but biomarkers are needed to guide optimal patient selection. The DNA repair protein MRE11 is a candidate response biomarker that has not been validated in prospective cohorts using standardized measurement approaches.

OBJECTIVE

To evaluate MRE11 expression as a prognostic biomarker in MIBC patients receiving trimodality therapy using automated quantitative image analysis.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study analyzed patients with MIBC pooled from 6 prospective phase I/II, II, or III trials of trimodality therapy (Radiation Therapy Oncology Group [RTOG] 8802, 8903, 9506, 9706, 9906, and 0233) across 37 participating institutions in North America from 1988 to 2007. Eligible patients had nonmetastatic MIBC and were enrolled in 1 of the 6 trimodality therapy clinical trials. Analyses were completed August 2020.

EXPOSURES

Trimodality therapy with transurethral bladder tumor resection and cisplatin-based chemoradiation therapy.

MAIN OUTCOMES AND MEASURES

MRE11 expression and association with disease-specific (bladder cancer) mortality (DSM), defined as death from bladder cancer. Pretreatment tumor tissues were processed for immunofluorescence with anti-MRE11 antibody and analyzed using automated quantitative image analysis to calculate a normalized score for MRE11 based on nuclear-to-cytoplasmic (NC) signal ratio.

RESULTS

Of 465 patients from 6 trials, 168 patients had available tissue, of which 135 were analyzable for MRE11 expression (median age of 65 years [minimum-maximum, 34-90 years]; 111 [82.2%] men). Median (minimum-maximum) follow-up for alive patients was 5.0 (0.6-11.7) years. Median (Q1-Q3) MRE11 NC signal ratio was 2.41 (1.49-3.34). Patients with an MRE11 NC ratio above 1.49 (ie, above first quartile) had a significantly lower DSM (HR, 0.50; 95% CI, 0.26-0.93; P = .03). The 4-year DSM was 41.0% (95% CI, 23.2%-58.0%) for patients with an MRE11 NC signal ratio of 1.49 or lower vs 21.0% (95% CI, 13.4%-29.8%) for a ratio above 1.49. MRE11 NC signal ratio was not significantly associated with overall survival (HR, 0.84; 95% CI, 0.49-1.44).

CONCLUSIONS AND RELEVANCE

Higher MRE11 NC signal ratios were associated with better DSM after trimodality therapy. Lower MRE11 NC signal ratios identified a poor prognosis subgroup that may benefit from intensification of therapy.

Quantitative measurement of HER2 expression to subclassify ERBB2 unamplified breast cancer

The efficacy of the antibody drug conjugate (ADC) Trastuzumab deruxtecan (T-DXd) in HER2 low breast cancer patients suggests that the historical/conventional assays for HER2 may need revision for optimal patient care. Specifically, the conventional assay is designed to distinguish amplified HER2 from unamplified cases but is not sensitive enough to stratify the lower ranges of HER2 expression. Here we determine the optimal dynamic range for unamplified HER2 detection in breast cancer and then redesign an assay to increase the resolution of the assay to stratify HER2 expression in unamplified cases. We used the AQUA™ method of quantitative immunofluorescence to test a range of antibody concentrations to maximize the sensitivity within the lower range of HER2 expression. Then, using a cell line microarray with HER2 protein measured by mass spectrometry we determined the amount of HER2 protein in units of attomols/mm². Then by calculation of the limits of detection, quantification, and linearity of this assay we determined that low HER2 range expression in unamplified cell lines is between 2 and 20 attomol/mm². Finally, application of this assay to a serial collection of 364 breast cancer cases from Yale shows 67% of the population has HER2 expression above the limit of quantification and below the levels seen in HER2 amplified breast cancer. In the future, this assay could be used to determine the levels of HER2 required for response to T-DXd or similar HER2 conjugated ADCs.

Quantitative assessment of Siglec-15 expression in lung, breast, head, and neck squamous cell carcinoma and bladder cancer

Immune checkpoint blockade with programmed cell death (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors has resulted in significant progress in the treatment of various cancer types. However, not all patients respond to PD-1/PD-L1 blockade, underscoring the importance of identifying new potential targets for immunotherapy. One promising target is the immune system modulator Siglec-15. In this study, we assess Siglec-15 expression in solid tumors, with a focus on lung, breast, head and neck squamous and bladder cancers. Using quantitative immunofluorescence (QIF) with a previously validated antibody, we found increased Siglec-15 expression in both tumor and immune cells in all the four cancer types. Siglec-15 was seen to be predominantly expressed by the stromal immune cells (83% in lung, 70.1% in breast, 95.2% in head and neck squamous cell and 89% in bladder cancers). Considerable intra-tumoral heterogeneity was noted across cancer types. As previously described for non-small cell lung cancer (NSCLC), Siglec-15 expression was seen to be mutually exclusive to PD-L1 in all the four cancer types, although this differential expression was maintained but somewhat diminished in head and neck squamous cell carcinoma (HNSCC). Siglec-15 was not prognostic either for overall survival (OS) or progression-free survival (PFS). In summary, we show broad expression of this potential immune modulatory target in a wide range of cancer types. These data suggest potential future clinical trials in these tumor types.

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

BACKGROUND

Most 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 study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC.

METHODS

We initially assessed a discovery cohort of 56 patients with NSCLC treated with PD-1 axis inhibitors at Yale Cancer Center. Using the GeoMx Digital Spatial Profiling (DSP) system, 71 proteins were measured in spatial context on each spot in a tissue microarray. We used the AQUA method of quantitative immunofluorescence (QIF) to orthogonally validate candidate biomarkers. For external independent validation, we assessed whole tissue sections derived from 128 patients with NSCLC treated with single-agent PD-1 axis inhibitors at the 12 de Octubre Hospital (Madrid) using DSP. We further analyzed two immunotherapy untreated cohorts to address prognostic significance (n=252 from Yale Cancer Center; n=124 from University Clinic of Navarra) using QIF and DSP, respectively.

RESULTS

Using continuous log-scaled data, we identified CD44 expression in the tumor compartment (pan-cytokeratin (CK)+) as a novel predictor of prolonged progression-free survival (PFS) (multivariate HR=0.68, p=0.043) in the discovery set. We validated by QIF that tumor CD44 levels assessed as continuous QIF scores were associated with longer PFS (multivariate HR=0.31, p=0.022) and overall survival (multivariate HR=0.29, p=0.038). Using DSP in an independent immunotherapy treated cohort, we validated that CD44 levels in the tumor compartment, but not in the immune compartment (panCK-/CD45+), were associated with clinical benefit (OR=1.22, p=0.018) and extended PFS under PD-1 axis inhibition using the highest tertile cutpoint (multivariate HR=0.62, p=0.03). The effect of tumor cell CD44 in predicting PFS remained significant after correcting for programmed death-ligand 1 (PD-L1) Tumor Proportion Score (TPS) in both cohorts. High tumor cell CD44 was not prognostic in the absence of immunotherapy. Using DSP data, intratumoral regions with elevated tumor cell CD44 expression showed prominent (fold change>1.5, adjusted p<0.05) upregulation of PD-L1, TIM-3, ICOS, and CD40 in two independent cohorts.

CONCLUSIONS

This work highlights CD44 as a novel indicative biomarker of sensitivity to PD-1 axis blockade that might help to improve immunotherapy strategies for NSCLC.

Discovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling

INTRODUCTION

Despite the clinical efficacy of immune checkpoint inhibitors (ICIs) in NSCLC, only approximately 20% of patients remain disease-free at 5 years. Here, we use digital spatial profiling to find candidate biomarker proteins associated with ICI resistance.

METHODS

Pretreatment samples from 56 patients with NSCLC treated with ICI were analyzed using the NanoString GeoMx digital spatial profiling method. A panel of 71 photocleavable oligonucleotide-labeled primary antibodies was used for protein detection in four molecular compartments (tumor, leukocytes, macrophages, and immune stroma). Promising candidates were orthogonally validated with quantitative immunofluorescence. Available pretreatment samples from 39 additional patients with NSCLC who received ICI and 236 non-ICI-treated patients with operable NSCLC were analyzed to provide independent cohort validation.

RESULTS

Biomarker discovery using the protein-based molecular compartmentalization strategy allows 284 protein variables to be assessed for association with ICI resistance by univariate analysis using continuous log-scaled data. Of the 71 candidate protein biomarkers, CD66b in the CD45+CD68 molecular compartment (immune stroma) predicted significantly shorter overall survival (OS) (hazard ratio [HR] 1.31, p = 0.016) and was chosen for validation. Orthogonal validation by quantitative immunofluorescence illustrated that CD66b was associated with resistance to ICI therapy but not prognostic for poor outcomes in untreated NSCLC (discovery cohort [OS HR 2.49, p = 0.026], validation cohort [OS HR 2.05, p = 0.046], non-ICI-treated cohort [OS HR 1.67, p = 0.06]).

CONCLUSIONS

Using the technique, we have discovered that CD66b expression is indicative of resistance to ICI therapy in NSCLC. Given that CD66b identifies neutrophils, further studies are warranted to characterize the role of neutrophils in ICI resistance.

Quantitative tissue analysis and role of myeloid cells in non-small cell lung cancer

BACKGROUND

Despite the prominent role of innate immunity in the antitumor response, little is known about the myeloid composition of human non-small cell lung cancer (NSCLC) with respect to histology and molecular subtype. We used multiplexed quantitative immunofluorescence (QIF) to measure the distribution and clinical significance of major myeloid cell subsets in large retrospective NSCLC collections.

METHODS

We established a QIF panel to map major myeloid cell subsets in fixed human NSCLC including 4',6-Diamidino-2-Phenylindole for all cells, pancytokeratin for tumor-epithelial cells, CD68 for M1-like macrophages; and CD11b plus HLA-DR to interrogate mature and immature myeloid cell populations such as myeloid derived suppressor cells (MDSCs). We interrogated 793 NSCLCs represented in four tissue microarray-based cohorts: #1 (Yale, n=379) and #2 (Greece, n=230) with diverse NSCLC subtypes; #3 (Yale, n=138) with molecularly annotated lung adenocarcinomas (ADC); and #4 (Yale, n=46) with patient-matched NSCLC and morphologically-normal lung tissue. We examined associations between marker levels, myeloid cell profiles, clinicopathologic/molecular variables and survival.

RESULTS

The levels of CD68+ M1 like macrophages were significantly lower and the fraction of CD11b+/HLA-DR- MDSC-like cells was prominently higher in tumor than in matched non-tumor lung tissues. HLA-DR was consistently higher in myeloid cells from tumors with elevated CD68 expression. Stromal CD11b was significantly higher in squamous cell carcinomas (SCC) than in ADC across the cohorts and EGFR-mutated lung ADCs displayed lower CD11b levels than KRAS-mutant tumors. Increased stromal CD68- and HLA-DR-expressing cells was associated with better survival in ADCs from two independent NSCLC cohorts. In SCC, increased stromal CD11b or HLA-DR expression was associated with a trend towards shorter 5-year survival.

CONCLUSIONS

NSCLCs display an unfavorable myeloid immune contexture relative to non-tumor lung and exhibit distinct myeloid-cell profiles across histologies and presence of major oncogenic driver-mutations. Elevated M1-like stromal proinflammatory myeloid cells are prognostic in lung ADC, but not in SCC.

Development of an immunohistochemical assay for Siglec-15

Siglec-15, a member of sialic-acid binding immunoglobulin type lectins, is normally expressed by myeloid cells and upregulated in some human cancers and represents a promising new target for immunotherapy. While PD-L1 blockade is an important strategy for immunotherapy, its effectiveness is limited. The expression of Siglec-15 has been demonstrated to be predominantly mutually exclusive to PD-L1 in certain cancer histologies. Thus, there is significant opportunity for Siglec-15 as an immunotherapeutic target for patients that do not respond to PD-1/PD-L1 inhibition. The aim of this study was to prospectively develop an immunohistochemical (IHC) assay for Siglec-15 to be used as a companion diagnostic for future clinical trials. Here, we create and validate an IHC assay with a novel recombinant antibody to the cytoplasmic domain of Siglec-15. To find an enriched target, this antibody was first used in a quantitative fluorescence (QIF) assay to screen a broad range of tumor histologies to determine tumor types where Siglec-15 demonstrated high expression. Based on this and previous data, we focused on development of a chromogenic IHC assay for lung cancer. Then we developed a scoring system for this assay that has high concordance amongst pathologist readers. We then use this chromogenic IHC assay to test the expression of Siglec-15 in two cohorts of NSCLC. We found that this assay shows a higher level of staining in both tumor and immune cells compared to previous QIF assays utilizing a polyclonal antibody. However, similar to that study, only a small percentage of positive Siglec-15 cases showed high expression for PD-L1. This validated assay for Siglec-15 expression may support development of a companion diagnostic assay to enrich for patients expressing the Siglec-15 target for therapy.

Multiplex Immunofluorescence and the Digital Image Analysis Workflow for Evaluation of the Tumor Immune Environment in Translational Research

A robust understanding of the tumor immune environment has important implications for cancer diagnosis, prognosis, research, and immunotherapy. Traditionally, immunohistochemistry (IHC) has been regarded as the standard method for detecting proteins in situ, but this technique allows for the evaluation of only one cell marker per tissue sample at a time. However, multiplexed imaging technologies enable the multiparametric analysis of a tissue section at the same time. Also, through the curation of specific antibody panels, these technologies enable researchers to study the cell subpopulations within a single immunological cell group. Thus, multiplexed imaging gives investigators the opportunity to better understand tumor cells, immune cells, and the interactions between them. In the multiplexed imaging technology workflow, once the protocol for a tumor immune micro environment study has been defined, histological slides are digitized to produce high-resolution images in which regions of interest are selected for the interrogation of simultaneously expressed immunomarkers (including those co-expressed by the same cell) by using an image analysis software and algorithm. Most currently available image analysis software packages use similar machine learning approaches in which tissue segmentation first defines the different components that make up the regions of interest and cell segmentation, then defines the different parameters, such as the nucleus and cytoplasm, that the software must utilize to segment single cells. Image analysis tools have driven dramatic evolution in the field of digital pathology over the past several decades and provided the data necessary for translational research and the discovery of new therapeutic targets. The next step in the growth of digital pathology is optimization and standardization of the different tasks in cancer research, including image analysis algorithm creation, to increase the amount of data generated and their accuracy in a short time as described herein. The aim of this review is to describe this process, including an image analysis algorithm creation for multiplex immunofluorescence analysis, as an essential part of the optimization and standardization of the different processes in cancer research, to increase the amount of data generated and their accuracy in a short time.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

A risk model of gene signatures for predicting platinum response and survival in ovarian cancer

Background

Ovarian cancer (OC) is the deadliest tumor in the female reproductive tract. And increased resistance to platinum-based chemotherapy represents the major obstacle in the treatment of OC currently. Robust and accurate gene expression models are crucial tools in distinguishing platinum therapy response and evaluating the prognosis of OC patients.

Methods

In this study, 230 samples from The Cancer Genome Atlas (TCGA) OV dataset were subjected to mRNA expression profiling, single nucleotide polymorphism (SNP), and copy number variation (CNV) analysis comprehensively to screen out the differentially expressed genes (DEGs). An SVM classifier and a prognostic model were constructed using the Random Forest algorithm and LASSO Cox regression model respectively via R. The Gene Expression Omnibus (GEO) database was applied as the validation set.

Results

Forty-eight differentially expressed genes (DEGs) were figured out through integrated analysis of gene expression, single nucleotide polymorphism (SNP), and copy number variation (CNV) data. A 10-gene classifier was constructed which could discriminate platinum-sensitive samples precisely with an AUC of 0.971 in the training set and of 0.926 in the GEO dataset (GSE638855). In addition, 8 optimal genes were further selected to construct the prognostic risk model whose predictions were consistent with the actual survival outcomes in the training cohort (p = 9.613e-05) and validated in GSE638855 (p = 0.04862). PNLDC1, SLC5A1, and SYNM were then identified as hub genes that were associated with both platinum response status and prognosis, which was further validated by the Fudan University Shanghai cancer center (FUSCC) cohort.

Conclusion

These findings reveal a specific risk model that could serve as effective biomarkers to identify patients’ platinum response status and predict survival outcomes for OC patients. PNLDC1, SLC5A1, and SYNM are the hub genes that may serve as potential biomarkers in OC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-022-00969-3.

Correlation of nuclear pIGF-1R/IGF-1R and YAP/TAZ in a tissue microarray with outcomes in osteosarcoma patients

Osteosarcoma (OS) is a genetically diverse bone cancer that lacks a consistent targetable mutation. Recent studies suggest the IGF/PI3K/mTOR pathway and YAP/TAZ paralogs regulate cell fate and proliferation in response to biomechanical cues within the tumor microenvironment. How this occurs and their implication upon osteosarcoma survival, remains poorly understood. Here, we show that IGF-1R can translocate into the nucleus, where it may act as part of a transcription factor complex. To explore the relationship between YAP/TAZ and total and nuclear phosphorylated IGF-1R (pIGF-1R), we evaluated sequential tumor sections from a 37-patient tissue microarray by confocal microscopy. Next, we examined the relationship between stained markers, clinical disease characteristics, and patient outcomes. The nuclear to cytoplasmic ratios (N:C ratio) of YAP and TAZ strongly correlated with nuclear pIGF-1R (r = 0.522, p = 0.001 for each pair). Kaplan-Meier analyses indicated that nuclear pIGF-1R predicted poor overall survival, a finding confirmed in the Cox proportional hazards model. Though additional investigation in a larger prospective study will be required to validate the prognostic accuracy of these markers, our results may have broad implications for the new class of YAP, TAZ, AXL, or TEAD inhibitors that have reached early phase clinical trials this year.

Impact of a randomized weight loss trial on breast tissue markers in breast cancer survivors

Few trials have examined the effect of lifestyle behavioral interventions on tissue markers in patients with cancer. The purpose of this study was to examine the feasibility and impact of a 6-month weight loss intervention on breast tissue and serum biomarkers in women with breast cancer. Fifty-one women who completed breast cancer treatment and had a BMI ≥ 25.0 kg/m² were randomized to a weight loss intervention or usual care. Breast tissue biopsies, fasting blood draw and body composition were collected at baseline and 6 months, with between-group changes examined using analysis of covariance method. Baseline and post-intervention biopsies were conducted in 49 and 42 women, respectively, with pre- and post-epithelial tissue available from 25 tissue samples. Average 6-month weight loss was 6.7% for the weight loss group and 2.0% increase for the usual care group (p < 0.0001). At baseline, body fat and serum insulin levels were inversely associated with breast tissue insulin receptor levels and CD68 (p < 0.05). At 6 months, favorable changes were observed in serum leptin and adiponectin levels and tissue CD163 among women randomized to weight loss vs. adverse change in women randomized to usual care (p < 0.05). Breast tissue biopsies are feasible to collect in a clinical research setting among breast cancer survivors, with weight loss favorably impacting metabolic and inflammatory markers associated with breast cancer.

An integrative approach of digital image analysis and transcriptome profiling to explore potential predictive biomarkers for TGFβ blockade therapy

Increasing evidence suggests that the presence and spatial localization and distribution pattern of tumor infiltrating lymphocytes (TILs) is associate with response to immunotherapies. Recent studies have identified TGFβ activity and signaling as a determinant of T cell exclusion in the tumor microenvironment and poor response to PD-1/PD-L1 blockade. Here we coupled the artificial intelligence (AI)-powered digital image analysis and gene expression profiling as an integrative approach to quantify distribution of TILs and characterize the associated TGFβ pathway activity. Analysis of T cell spatial distribution in the solid tumor biopsies revealed substantial differences in the distribution patterns. The digital image analysis approach achieves 74% concordance with the pathologist assessment for tumor-immune phenotypes. The transcriptomic profiling suggests that the TIL score was negatively correlated with TGFβ pathway activation, together with elevated TGFβ signaling activity observed in excluded and desert tumor phenotypes. The present results demonstrate that the automated digital pathology algorithm for quantitative analysis of CD8 immunohistochemistry image can successfully assign the tumor into one of three infiltration phenotypes: immune desert, immune excluded or immune inflamed. The association between “cold” tumor-immune phenotypes and TGFβ signature further demonstrates their potential as predictive biomarkers to identify appropriate patients that may benefit from TGFβ blockade.

Advances in mass cytometry and its applicability to digital pathology in clinical-translational cancer research

The development and subsequent adaptation of mass cytometry for the histological analysis of tissue sections has allowed the simultaneous spatial characterization of multiple components. This is useful to find the correlation between the genotypic and phenotypic profile of tumor cells and their environment in clinical-translational studies. In this revision, we provide an overview of the most relevant hallmarks in the development, implementation and application of multiplexed imaging in the study of cancer and other conditions. A special focus is placed on studies based on imaging mass cytometry (IMC) and multiplexed ion beam imaging (MIBI). The purpose of this review is to help our readers become familiar with the verification techniques employed on this tool and outline the multiple applications reported in the literature. This review will also provide guidance on the use of IMC or MIBI in any field of biomedical research.

Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.

Fluorescent Immunohistochemistry

Immunofluorescence is an important immunochemical technique that utilizes fluorescence-labeled antibodies to detect specific target antigens. It is used widely in both scientific research and clinical laboratories. Immunofluorescence allows for excellent sensitivity and amplification of signal in comparison to immunohistochemistry. However, analysis of samples labeled with fluorescence-labeled antibodies has to be performed using a fluorescence microscope or other type of fluorescence imaging. There are two methods available: direct (primary) and indirect (secondary) immunofluorescence. Here, we describe the principle of immunofluorescence methods as well as the preparation of fresh-frozen and formalin-fixed, paraffin embedded tissues for both direct and indirect immunofluorescence labeling.

Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case-control study

PURPOSE

Triple negative breast cancer (TNBC) is more common in African American (AA) than Non-AA (NAA) population. We hypothesize that tumor microenvironment (TME) contributes to this disparity. Here, we use multiplex quantitative immunofluorescence to characterize the expression of immunologic biomarkers in the TME in both populations.

PATIENTS AND METHODS

TNBC tumor resection specimen tissues from a 100-patient case: control cohort including 49 AA and 51 NAA were collected. TME markers including CD45, CD14, CD68, CD206, CD4, CD8, CD20, CD3, Ki67, GzB, Thy1, FAP, aSMA, CD34, Col4, VWF and PD-L1 we quantitatively assessed in every field of view. Mean expression levels were compared between cases and controls.

RESULTS

Although no significant differences were detected in individual lymphoid and myeloid markers, we found that infiltration with CD45+ immune cells (p = 0.0102) was higher in TNBC in AA population. AA TNBC tumors also had significantly higher level of lymphocytic infiltration defined as CD45+ CD14- cells (p = 0.0081). CD3+ T-cells in AA tumors expressed significantly higher levels of Ki67 (0.0066) compared to NAAs, indicating that a higher percentage of AA tumors contained activated T-cells. All other biomarkers showed no significant differences between the AA and NAA group.

CONCLUSIONS

While the TME in TNBC is rich in immune cells in both racial groups, there is a numerical increase in lymphoid infiltration in AA compared to NAA TNBC. Significantly, higher activated T cells seen in AA patients raises the possibility that there may be a subset of AA patients with improved response to immunotherapy.

Spatial protein heterogeneity analysis in frozen tissues to evaluate tumor heterogeneity

A new workflow for protein-based tumor heterogeneity probing in tissues is here presented. Tumor heterogeneity is believed to be key for therapy failure and differences in prognosis in cancer patients. Comprehending tumor heterogeneity, especially at the protein level, is critical for tracking tumor evolution, and showing the presence of different phenotypical variants and their location with respect to tissue architecture. Although a variety of techniques is available for quantifying protein expression, the heterogeneity observed in the tissue is rarely addressed. The proposed method is validated in breast cancer fresh-frozen tissues derived from five patients. Protein expression is quantified on the tissue regions of interest (ROI) with a resolution of up to 100 μm in diameter. High heterogeneity values across the analyzed patients in proteins such as cytokeratin 7, β-actin and epidermal growth factor receptor (EGFR) using a Shannon entropy analysis are observed. Additionally, ROIs are clustered according to their expression levels, showing their location in the tissue section, and highlighting that similar phenotypical variants are not always located in neighboring regions. Interestingly, a patient with a phenotype related to increased aggressiveness of the tumor presents a unique protein expression pattern. In summary, a workflow for the localized extraction and protein analysis of regions of interest from frozen tissues, enabling the evaluation of tumor heterogeneity at the protein level is presented.

Alpha-smooth Muscle Actin Expression in the Stroma Predicts Resistance to Trastuzumab in Patients with Early-stage HER2-positive Breast Cancer

PURPOSE

The companion diagnostic test for trastuzumab has not changed much in the last 25 years. We used high-plex digital spatial profiling to identify biomarkers besides HER2 that can help predict response to trastuzumab in HER2-positive breast cancer.

EXPERIMENTAL DESIGN

Fifty-eight protein targets were measured in three different molecularly defined compartments by the NanoString GeoMx Digital Spatial Profiler (DSP) in a tissue microarray containing 151 patients with breast cancer that received adjuvant trastuzumab as part of the Hellenic Cooperative Oncology Group 10/05 clinical trial. Promising candidate biomarkers were orthogonally validated with quantitative immunofluorescence (QIF). RNA-sequencing data from the Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimisation Study (NeoALTTO) were accessed to provide independent cohort validation. Disease-free survival (DFS) was the main outcome assessed. Statistical analyses were performed using a two-sided test (α = 0.05) and multiple testing correction (Benjamini-Hochberg method, FDR < 0.1).

RESULTS

By DSP, high expression of alpha-smooth muscle actin (α-SMA), both in the leukocyte and stromal compartments, was associated with shorter DFS in univariate analysis (P = 0.002 and P = 0.023, respectively). High α-SMA expression in the stroma was validated by QIF after controlling for estrogen receptor and progesterone receptor status [HR, 3.12; 95% confidence interval (CI), 1.12-8.68; P = 0.029] showing recurrence on trastuzumab in the same cohort. In the NeoALTTO cohort, elevated levels of ACTA2 were predictive for shorter DFS in the multivariate analysis (HR, 3.21; 95% CI, 1.14-9.05; P = 0.027).

CONCLUSIONS

This work identifies α-SMA as a novel, easy-to-implement biomarker of resistance to trastuzumab that may be valuable in settings where trastuzumab is combined with other therapies.

Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes, Cancer-Associated Fibroblasts, and CD200 in Pancreatic Cancer

Pancreatic cancer is marked by a desmoplastic tumor microenvironment and low tumor immunogenicity, making it difficult for immunotherapy drugs to improve outcomes for patients. Tumor-infiltrating lymphocytes (TILs) and cancer-associated fibroblasts (CAFs) are seen in the tumor microenvironment of patients with pancreatic ductal adenocarcinoma (PDAC). In this work, we sought to characterize the expression levels and potential prognostic value of TILs (CD4, CD8, and CD20) and CAFs (Thy-1, FAP, and SMA) in a large retrospective cohort of PDAC patients. Additionally, we investigated the expression levels and prognostic significance of CD200, an immunoinhibitory protein that has shown interest as a potential target for immune checkpoint blockade. We measured the expression levels of these seven proteins with multiplexed immunofluorescence staining and quantitative immunofluorescence (QIF). We found CD8 and FAP to be independent predictors of progression-free survival and overall survival. CD200 was found to be heterogeneously expressed in both the tumor and stromal compartments of PDAC, with the majority of patients having positive stromal expression and negative tumor expression. This work demonstrates the potential clinical utility of CD8 and FAP in PDAC patients, and it sheds light on the expression patterns of CD200 in pancreatic cancer as the protein is being tested as a target for immune checkpoint blockade.

Spatially resolved analysis of the T cell immune contexture in lung cancer-associated brain metastases

Despite unique genetic alterations within brain metastases (BrMs) and an immunologically distinct surrounding microenvironment, the composition and functional properties of tumor-infiltrating lymphocytes within BrM remain largely unexplored. In particular, the expression of coinhibitory receptors, such as programmed cell death 1 (PD-1), T cell immunoglobulin mucin receptor 3 (TIM-3), and lymphocyte activation gene 3 (LAG-3), within BrMs is unknown. Using multiplexed quantitative immunofluorescence (QIF), this study evaluates the localized expression of PD-L1, level and functional profile of major T cell subsets, and coinhibitory receptors within lung cancer-associated BrMs and primary lung tumors. Clinicopathologically annotated samples from 95 patients with lung cancer between 2002 and 2015 were represented in a tissue microarray format. Spatially resolved and multiplexed QIF was used to evaluate PD-L1 protein, phenotype markers for major T cell subsets (CD3, CD4, CD8, and FOXP3), cell-localized activation and proliferation markers (granzyme B and Ki67), and coinhibitory receptors (PD-1, LAG-3, and TIM-3). The signal for each marker was measured in marker-selected tissue compartments, and associations between marker levels, tumor location, and major clinicopathological variables were studied. In total, 41 primary lung tumors and 65 BrMs were analyzed, including paired samples from 11 patients. Levels of tumor PD-L1 expression were comparable between BrMs and primary lung tumors. BrMs had significantly lower levels of all T cell subsets relative to primary lung tumors, and T cells in BrMs displayed lower levels of granzyme B than primary lesions. PD-1, TIM-3, and LAG-3 levels in CD3⁺ T-cells were also significantly lower in BrMs. Marker expression in patients with paired samples from BrMs and primary lung tumors showed comparable results. High CD3⁺ T-cells, as well as high levels of TIM-3 and LAG-3 in CD3⁺ T-cells, were associated with longer overall survival in BrMs but not primary lung tumors. Lung cancer-associated BrMs display lower T cell infiltration, markers of cytolytic function, and immune regulatory signals than primary lung tumors. Despite these differences, high TIM-3 and high LAG-3 expressions in CD3⁺ T-cells were associated with longer survival. These features are accompanied by comparable levels of PD-L1 protein expression compared with primary lung tumors. These results highlight unique aspects of the tumor immune microenvironment within the brain and provide further support for intracranially focused therapies.

Pixelwise H-score: A novel digital image analysis-based metric to quantify membrane biomarker expression from immunohistochemistry images

Immunohistochemistry (IHC) assays play a central role in evaluating biomarker expression in tissue sections for diagnostic and research applications. Manual scoring of IHC images, which is the current standard of practice, is known to have several shortcomings in terms of reproducibility and scalability to large scale studies. Here, by using a digital image analysis-based approach, we introduce a new metric called the pixelwise H-score (pix H-score) that quantifies biomarker expression from whole-slide scanned IHC images. The pix H-score is an unsupervised algorithm that only requires the specification of intensity thresholds for the biomarker and the nuclear-counterstain channels. We present the detailed implementation of the pix H-score in two different whole-slide image analysis software packages Visiopharm and HALO. We consider three biomarkers P-cadherin, PD-L1, and 5T4, and show how the pix H-score exhibits tight concordance to multiple orthogonal measurements of biomarker abundance such as the biomarker mRNA transcript and the pathologist H-score. We also compare the pix H-score to existing automated image analysis algorithms and demonstrate that the pix H-score provides either comparable or significantly better performance over these methodologies. We also present results of an empirical resampling approach to assess the performance of the pix H-score in estimating biomarker abundance from select regions within the tumor tissue relative to the whole tumor resection. We anticipate that the new metric will be broadly applicable to quantify biomarker expression from a wide variety of IHC images. Moreover, these results underscore the benefit of digital image analysis-based approaches which offer an objective, reproducible, and highly scalable strategy to quantitatively analyze IHC images.

Targeting Pyruvate Kinase M2 Phosphorylation Reverses Aggressive Cancer Phenotypes

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low survival rate and a lack of biomarkers and targeted treatments. Here, we target pyruvate kinase M2 (PKM2), a key metabolic component of oncogenesis. In patients with TNBC, PKM2pS37 was identified as a prominent phosphoprotein corresponding to the aggressive breast cancer phenotype that showed a characteristic nuclear staining pattern and prognostic value. Phosphorylation of PKM2 at S37 was connected with a cyclin-dependent kinase (CDK) pathway in TNBC cells. In parallel, pyruvate kinase activator TEPP-46 bound PKM2pS37 and reduced its nuclear localization. In a TNBC mouse xenograft model, treatment with either TEPP-46 or the potent CDK inhibitor dinaciclib reduced tumor growth and diminished PKM2pS37. Combinations of dinaciclib with TEPP-46 reduced cell invasion, impaired redox balance, and triggered cancer cell death. Collectively, these data support an approach to identify PKM2pS37-positive TNBC and target the PKM2 regulatory axis as a potential treatment. SIGNIFICANCE: PKM2 phosphorylation marks aggressive breast cancer cell phenotypes and targeting PKM2pS37 could be an effective therapeutic approach for treating triple-negative breast cancer.

Reliability of a computational platform as a surrogate for manually interpreted immunohistochemical markers in breast tumor tissue microarrays

BACKGROUND

Pathologist and computational assessments have been used to evaluate immunohistochemistry (IHC) in epidemiologic studies. We compared Definiens Tissue Studio® to pathologist scores for 17 markers measured in breast tumor tissue microarrays (TMAs) [AR, CD20, CD4, CD8, CD163, EPRS, ER, FASN, H3K27, IGF1R, IR, Ki67, phospho-mTOR, PR, PTEN, RXR, and VDR].

METHODS

5 914 Nurses' Health Study participants, diagnosed 1976-2006 (NHS) and 1989-2006 (NHS-II), were included. IHC was conducted by the Dana-Farber/Harvard Cancer Center Specialized Histopathology Laboratory. The percent of cells staining positive was assessed by breast pathologists. Definiens output was used to calculate a weighted average of percent of cells staining positive across TMA cores for each marker. Correlations between pathologist and computational scores were evaluated with Spearman correlation coefficients. Receiver-operator characteristic curves were constructed, using pathologist scores as comparison.

RESULTS

Spearman correlations between pathologist and Definiens assessments ranged from weak (RXR, rho=-0.05; CD163, rho = 0.10) to strong (Ki67, rho = 0.79; pmTOR, rho = 0.77). The area under the curve was >0.70 for all markers except RXR.

CONCLUSION

Our data indicate that computational assessments exhibit variable correlations with interpretations made by an expert pathologist, depending on the marker evaluated. This study provides evidence supporting the use of computational platforms for IHC evaluation in large-scale epidemiologic studies, with the caveat that pilot studies are necessary to investigate agreement with expert assessments. In sum, computational platforms may provide greater efficiency and facilitate high-throughput epidemiologic analyses.

Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER+ Breast Cancer

PURPOSE

FGFR1 overexpression has been associated with endocrine resistance in ER⁺ breast cancer. We found FGFR1 localized in the nucleus of breast cancer cells in primary tumors resistant to estrogen suppression. We investigated a role of nuclear FGFR1 on gene transcription and antiestrogen resistance.

EXPERIMENTAL DESIGN

Tumors from patients treated with letrozole were subjected to Ki67 and FGFR1 IHC. MCF7 cells were transduced with FGFR1(SP-)(NLS) to promote nuclear FGFR1 overexpression. FGFR1 genomic activity in ER⁺/FGFR1-amplified breast cancer cells ± FOXA1 siRNA or ± the FGFR tyrosine kinase inhibitor (TKI) erdafitinib was examined by chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-seq). The nuclear and chromatin-bound FGFR1 interactome was investigated by mass spectrometry (MS).

RESULTS

High nuclear FGFR1 expression in ER⁺ primary tumors positively correlated with post-letrozole Ki67 values. Nuclear FGFR1 overexpression influenced gene transcription and promoted resistance to estrogen suppression and to fulvestrant in vivo. A gene expression signature induced by nuclear FGFR1 correlated with shorter survival in the METABRIC cohort of patients treated with antiestrogens. ChIP-Seq revealed FGFR1 occupancy at transcription start sites, overlapping with active transcription histone marks. MS analysis of the nuclear FGFR1 interactome identified phosphorylated RNA-Polymerase II and FOXA1, with FOXA1 RNAi impairing FGFR1 recruitment to chromatin. Treatment with erdafitinib did not impair nuclear FGFR1 translocation and genomic activity.

CONCLUSIONS

These data suggest nuclear FGFR1 contributes to endocrine resistance by modulating gene transcription in ER⁺ breast cancer. Nuclear FGFR1 activity was unaffected by FGFR TKIs, thus supporting the development of treatment strategies to inhibit nuclear FGFR1 in ER+/FGFR1 overexpressing breast cancer.

Heterogenous presence of neutrophil extracellular traps in human solid tumours is partially dependent on IL-8

Neutrophil extracellular traps (NETs) are webs of extracellular nuclear DNA extruded by dying neutrophils infiltrating tissue. NETs constitute a defence mechanism to entrap and kill fungi and bacteria. Tumours induce the formation of NETs to the advantage of the malignancy via a variety of mechanisms shown in mouse models. Here, we investigated the presence of NETs in a variety of human solid tumours and their association with IL-8 (CXCL8) protein expression and CD8⁺ T-cell density in the tumour microenvironment. Multiplex immunofluorescence panels were developed to identify NETs in human cancer tissues by co-staining with the granulocyte marker CD15, the neutrophil marker myeloperoxidase and citrullinated histone H3 (H3Cit), as well as IL-8 protein and CD8⁺ T cells. Three ELISA methods to detect and quantify circulating NETs in serum were optimised and utilised. Whole tumour sections and tissue microarrays from patients with non-small cell lung cancer (NSCLC; n = 14), bladder cancer (n = 14), melanoma (n = 11), breast cancer (n = 31), colorectal cancer (n = 20) and mesothelioma (n = 61) were studied. Also, serum samples collected retrospectively from patients with metastatic melanoma (n = 12) and NSCLC (n = 34) were ELISA assayed to quantify circulating NETs and IL-8. NETs were detected in six different human cancer types with wide individual variation in terms of tissue density and distribution. At least in NSCLC, bladder cancer and metastatic melanoma, NET density positively correlated with IL-8 protein expression and inversely correlated with CD8⁺ T-cell densities. In a series of serum samples from melanoma and NSCLC patients, a positive correlation between circulating NETs and IL-8 was found. In conclusion, NETs are detectable in formalin-fixed human biopsy samples from solid tumours and in the circulation of cancer patients with a considerable degree of individual variation. NETs show a positive association with IL-8 and a trend towards a negative association with CD8⁺ tumour-infiltrating lymphocytes. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Spatially Resolved and Quantitative Analysis of the Immunological Landscape in Human Meningiomas

The immunological status of human meningiomas is not well understood, hindering the development of rational immunotherapeutic strategies. We measured the levels of PD-L1, PD-L2, and immune cell subsets using multiplex quantitative immunofluorescence in a tissue microarray composed of 73 human meningiomas (56 WHO Grade 1, 13 WHO Grade 2, and 4 WHO Grade 3). We analyzed tumor-infiltrating immune cell populations, T-cell activation/dysfunction, and macrophage phenotypes. PD-L1 and PD-L2 were detected in 5.8% and 68.7% of cases, respectively. There was a higher PD-L1 expression in CD68+ macrophages compared with tumor cells (p < 0.001). There was a weak positive correlation between PD-L1 expression and CD3+ T-cell infiltration. The level of CD3+ cells and T-cell activation/proliferation in human meningiomas were highly variable with an increased CD4-to-CD8 ratio in higher grade tumors (p < 0.05). There was a stronger correlation between GZMB/Ki67 with PD-L2 than PD-L1. We found that 15.23%, 6.66%, and 5.49% of macrophages were CD163+, CD68+, and CD163+CD68+, respectively. In cases where there is high CD3+ T-cell infiltration, 23.5% and 76.5% had dormant and activated T-cell phenotypes, respectively. We conclude that human meningiomas are either PD-L1low TILlow or PD-L1low TILhigh tumors and harbor variable TIL infiltration and phenotypes.

BRCA1 Protein Expression Predicts Survival in Glioblastoma Patients from an NRG Oncology RTOG Cohort

PURPOSE

Glioblastoma, the most common malignant brain tumor, was associated with a median survival of <1 year in the pre-temozolomide (TMZ) era. Despite advances in molecular and genetic profiling studies identifying several predictive biomarkers, none has been translated into routine clinical use. Our aim was to investigate the prognostic significance of a panel of diverse cellular molecular markers of tumor formation and growth in an annotated glioblastoma tissue microarray (TMA).

METHODS AND MATERIALS

A TMA composed of archived glioblastoma tumors from patients treated with surgery, radiation, and non-TMZ chemother-apy, was provided by RTOG. RAD51, BRCA-1, phosphatase and tensin homolog tumor suppressor gene (PTEN), and miRNA-210 expression levels were assessed using quantitative in situ hybridization and automated quantitative protein analysis. The objectives of this analysis were to determine the association of each biomarker with overall survival (OS), using the Cox proportional hazard model. Event-time distributions were estimated using the Kaplan-Meier method and compared by the log-rank test.

RESULTS

A cohort of 66 patients was included in this study. Among the 4 biomarkers assessed, only BRCA1 expression had a statistically significant correlation with survival. From univariate analysis, patients with low BRCA1 protein expression showed a favorable outcome for OS (p = 0.04; hazard ratio = 0.56) in comparison with high expressors, with a median survival time of 18.9 versus 4.8 months.

CONCLUSIONS

BRCA1 protein expression was an important survival predictor in our cohort of glioblastoma patients. This result may imply that low BRCA1 in the tumor and the consequent low level of DNA repair cause vulnerability of the cancer cells to treatment.

Targeting the CSF1/CSF1R Axis is a Potential Treatment Strategy for Malignant Meningiomas

BACKGROUND

Malignant meningiomas are fatal and lack effective therapy. As M2 macrophages are the most prevalent immune cell type in human meningiomas, we hypothesized that normalizing this immunosuppressive population would be an effective treatment strategy.

METHODS

We used CIBERSORTX to examine the proportions of 22 immune subsets in human meningiomas. We targeted the colony stimulating factor 1 (CSF1) or CSF1 receptor (CSF1R) axis, an important regulator of macrophage phenotype, using monoclonal antibodies (mAbs) in a novel immunocompetent murine model (MGS1) for malignant meningioma. RNA-seq was performed to identify changes in gene expression in the tumor microenvironment. Mass cytometry was used to delineate changes in immune subsets after treatment. We measured patients' plasma CSF1 levels using ELISA and CSF1R expression using multiplex quantitative immunofluorescence in a human meningioma tissue microarray.

RESULTS

Human meningiomas are heavily enriched for immunosuppressive myeloid cells. MGS1 recapitulates the tumor microenvironment of human meningiomas, including an abundance of myeloid cells, a paucity of infiltrating T cells, and low programmed-death ligand 1 (PD-L1) expression. Treatment of murine meningiomas with anti-CSF1/CSF1R, but not programmed cell death receptor 1 (PD-1), mAbs abrogate tumor growth. RNA-seq and mass cytometry analyses reveal a myeloid cell reprogramming with limited effect on T cells in the tumor microenvironment. CSF1 plasma levels are significantly elevated in human patients and CSF1R is highly expressed on CD163 + macrophages within the human tumor microenvironment.

CONCLUSION

Our findings suggests that anti-CSF1/CSF1R antibody treatment may be an effective normalization cancer immunotherapy for malignant meningiomas.

STING enhances cell death through regulation of reactive oxygen species and DNA damage

Resistance to DNA-damaging agents is a significant cause of treatment failure and poor outcomes in oncology. To identify unrecognized regulators of cell survival we performed a whole-genome CRISPR-Cas9 screen using treatment with ionizing radiation as a selective pressure, and identified STING (stimulator of interferon genes) as an intrinsic regulator of tumor cell survival. We show that STING regulates a transcriptional program that controls the generation of reactive oxygen species (ROS), and that STING loss alters ROS homeostasis to reduce DNA damage and to cause therapeutic resistance. In agreement with these data, analysis of tumors from head and neck squamous cell carcinoma patient specimens show that low STING expression is associated with worse outcomes. We also demonstrate that pharmacologic activation of STING enhances the effects of ionizing radiation in vivo, providing a rationale for therapeutic combinations of STING agonists and DNA-damaging agents. These results highlight a role for STING that is beyond its canonical function in cyclic dinucleotide and DNA damage sensing, and identify STING as a regulator of cellular ROS homeostasis and tumor cell susceptibility to reactive oxygen dependent, DNA damaging agents.

Preparation, construction and high-throughput automated analysis of human brain tissue microarrays for neurodegenerative disease drug development

A major challenge in the treatment of neurodegenerative disorders is the translation of effective therapies from the lab to the clinic. One approach to improve this process is the use of human brain tissue microarray (HBTMA) technology to aid in the discovery and validation of drug targets for brain disorders. In this protocol we describe a platform for the production of high-quality HBTMAs that can be used for drug target discovery and validation. We provide examples of the use of this platform and describe detailed protocols for HBTMA design, construction and use for both protein and mRNA detection. This platform requires less tissue and reagents than single-slide approaches, greatly increasing throughput and capacity, enabling samples to be compared in a more consistent way. It takes 4 d to construct a 60 core HBTMA. Immunohistochemistry and in situ hybridization take a further 2 d. Imaging of each HBTMA slide takes 15 min, with subsequent high-content analysis taking 30 min-2 h.