Tissue Microarray Cores Research Articles

Abstract 34: Predictors of discordance between image-based and manual scoring of immunohistochemical stains in ovarian cancer tissue microarrays

Abstract Digital image-based scoring of immunohistochemistry (IHC) staining allows faster, more objective and potentially more reproducible quantification of area stained or cell counts compared to manual scoring. However, predictors of discrepancies between these two assessment methods are not well understood. We examined clinical and pathological characteristics associated with discordance between image-based and manual scoring using ovarian cancer tissue microarrays (TMA) across a range of IHC stains. We evaluated 2,159 TMA cores from 681 ovarian cancer cases stained by four tissue cytoplasmic stains quantified as percentage of the tumor area stained (POSTN, CXCL14, ADH1B, COL11A1) and two immune cell markers quantified by cell count of infiltrating immune cells (CD68, CD163). The TMA slides were scored manually using semi-quantitative scoring by gynecologic pathologists as well as digitally using image-based Definiens automated platform. We used generalized linear mixed models with individual patients and TMAs included as random effects and stain as fixed effect to examine predictors of discordance, defined as absolute difference of ≥1SD in z-scores between image-based and manual scoring, overall and by each stain. The multi-level model included characteristics of the TMA, core, and tumor factors as predictors. Overall, TMA construction by automated robotic system (vs manual), smaller core size or area, borderline (vs invasive tumors), and having no geographic necrosis in the tumor were significantly associated with greater discordance between image-based and manual scoring. Interestingly, all these factors, except geographic necrosis, were differentially associated with discordance across the stains (p-interaction <0.05). Having multiple loci of geographic necrosis was associated with less discordance (OR=0.84, 95%CI=0.72-0.97). Invasive tumors compared to borderline tumors were less likely to be discordantly scored overall (OR=0.80, 95%CI=0.65-1.00) and for tissue cytoplasmic stains (OR range: 0.42-0.73), with associations in the opposite direction for immune cell markers (OR range: 1.21-2.37). Core areas in the lowest quartile vs all other cores were associated with greater discordance (OR=1.18, 95%CI=1.05-1.32), which was more notable for the tissue cytoplasmic stains (OR range: 1.18-2.00) compared to immune cell markers (OR range: 0.83-0.86). TMAs created by robot vs by hand had 64% higher odds of discordance (95%CI=1.20-2.25), which was more apparent when blank rows and columns were included on the TMA. Overall, TMA, core, and tumor level factors were related to discordance between image-based and manual scoring. Some stain types may be more susceptible to specific pre-analytic factors suggesting that reproducibility studies of manual vs image-based scoring should be conducted on a proportion of cases in large scale projects. Citation Format: Naoko Sasamoto, Mary Townsend, Farnoosh Abbas-Aghababazadeh, Kathryn L. Terry, Joseph O. Johnson, Jonathan L. Hecht, Brooke L. Fridley, Shelley S. Tworoger. Predictors of discordance between image-based and manual scoring of immunohistochemical stains in ovarian cancer tissue microarrays [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 34.

Abstract 4976: Combining measures of immune infiltration uncovers predictors of survival in high-grade serous ovarian cancer

Abstract Background: In colorectal and breast cancer, the density and localization of immune infiltrates provides strong prognostic information. We asked whether similar automated quantitation and combined analysis of immune infiltrates could refine prognostic information in high-grade serous ovarian carcinoma (HGSOC) and tested associations between patterns of immune response and genomic driver alterations. Methods and Findings: Epithelium and stroma were semi-automatically segmented and the infiltration of CD45RO+, CD8+ and CD68+ cells was automatically quantified from images of 332 HGSOC patient tissue microarray cores. Epithelial CD8 (p=0.027, HR=0.83), stromal CD68 (p=3 × 10-4, HR=0.44) and stromal CD45RO (p=7 × 10-4, HR=0.76) were positively associated with survival and remained so when averaged across the tumor and stromal compartments.Using principal component analysis (PCA), we identified optimized multiparameter survival models that combined information from all immune markers (p=0.016, HR=0.88). There was no significant association between PTEN expression, type of TP53 mutation or presence of BRCA1/BRCA2 mutations and immune infiltrate densities or principal components. Conclusions: Combining measures of immune infiltration provided improved survival modeling and evidence for the multiple effects of different immune factors on survival. The presence of stromal CD68+ and CD45RO+ populations was strongly associated with survival, underscoring the benefits that evaluating stromal immune populations may bring for prognostic immunoscores in HGSOC. Citation Format: Anne Montfort, Steph J. Owen, Anna M. Piskorz, Anna Supernat, Luiza Moore, Sarwah Al-Khalidi, Steffen Boehm, Paul Pharoah, Jacqueline McDermott, Frances R. Balkwill, James D. Brenton. Combining measures of immune infiltration uncovers predictors of survival in high-grade serous ovarian cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4976.

Role of CD8+ T-cell infiltration in breast tumors of Black women compared to White women.

e13608 Background: Literature regarding racial differences in tumor immune responses in breast cancer remains sparse. To address this research gap, we assessed CD8+ T-cells in breast tumor samples from the Women’s Circle of Health Study (WCHS) population of predominantly Black breast cancer patients. We characterized and compared the density of CD8+ T cells, their prognostic value and their association with pharmacologic beta-blockers. Prior studies suggest that reducing adrenergic signaling through beta blockers can stimulate CD8+ T-cells. Methods: Tumor-infiltrating CD8+ T-cells were assessed by IHC staining of tissue microarray cores from 688 breast cancer patients, including 550 Blacks and 138 Whites. CD8+ T cells were scored with digital image analysis. Comparisons of demographic and clinical variables (including CD8+ T cell density) were made using the Mann-Whitney U or Kruskal-Wallis and Fisher’s exact tests. Associations with overall survival (OS) and disease-specific (DSS) survival were evaluated using the log-rank test of Cox regression. Analyses were performed in the overall sample and by disease sub-type. Results: Higher CD8+ T cell density was seen in Black women compared to White, with mean values of 756.2/mm2 and 292.4/mm2 respectively (p < 0.001). Within the overall population and in black women, CD8+ T cell density was significantly higher in younger patients, patients with high grade, and ER negative tumors. No significant associations were observed between CD8+ T cell density and OS or DSS. However, when stratified by subtype, Black patients with triple negative breast cancer and high CD8+ T cell density showed a trend towards improved OS in comparison to patients with low CD8+ T cell density (p = 0.065). 170 patients with information on beta blocker usage were analyzed. No significant associations were noted between CD8+ T cell density and beta blocker use. Conclusions: We observe a significantly higher CD8+ T cell density in Blacks compared to Whites, but this does not confer a survival advantage. Additionally, beta-blockers did not seem to enhance CD8+ T cell infiltration in tumors from Black patients. Our data raise the possibility that distinct mechanisms of immune cell action may occur in different racial groups. Future studies are needed to determine the functional properties of CD8+ T cells in Black women and to characterize additional immune cell subtypes that may also play a role.

A METHOD FOR DIGITAL QUANTIFICATION OF EOSINOPHILS INFILTRATE IN ORAL SQUAMOUS CELL CARCINOMA

Introduction:The recent advances in tumor immunotherapy triggered more attention towards analysis of tumor inflammation. Oral squamous cell carcinoma (OSCC) is malignancy that can be therapeutically challenging and resistant to treatment. Further investigation of the inflammatory profile in OSCC can enhance our understanding of the disease and hence patient response to immunotherapy. Eosinophils are suggested to play a significant role in tumor progression and have been described to be associated with advanced stage malignancies of several tumor subtypes. Objective: Here we wanted to assess a methodology to quantitatively measure eosinophils infiltrate in OSCC. Material and methods: Eosinophils infiltrate was analyzed in formalin fixed paraffin embedded tissue (FFPE) microarray cores of 30 oral squamous cell carcinomas (OSCC), and 10 normal oral epithelium controls. Digital analysis using the auto fluorescence of eosinophils accentuated by Alexa Fluor 488 stain, in FFPE tissue sections; we used Cytation 5 machine and Gen 5 software, to digitally quantify the extent of eosinophils infiltrate in OSCC. Results: Out of the inflamed OSCC examined sections with heavy inflammatory infiltrate rich in eosinophils, RBCs, neutrophils and monocytes, eosinophils were readily detected, and digitally quantified after staining with Alexa Fluor 488. The tumor cores showed eosinophils infiltrate in the peri-tumoral stroma of 26 (87%) of the 30 examined OSCC Conclusion: This study highlights the importance of assessment of the type and extent of inflammatory cells infiltrate as well as its digital quantification. It provides a novel quantification method of eosinophils that opens avenues to study the correlation between eosinophils infiltrate and tumor prognosis.

Correlation between the expression of folate receptor alpha (FRα) and clinicopathological features in patients with lung adenocarcinoma

ObjectivesFolate receptor alpha (FRα) is expressed on the cell surface, mediates its intracellular transport via receptor-mediated endocytosis, and is involved in cell division. Whether FRα could be a potential therapeutic target in FRα-expressing cancers remains unknown. Here, we retrospectively investigated the correlations between tumor FRα expression in lung adenocarcinoma (LADC) and clinicopathological features. Materials and methodsFRα expression was evaluated using a tissue microarray (TMA) constructed from surgical specimens of LADC and compared with clinicopathological features including the EGFR mutation status and the expressions of PD-L1, PD-L2, PD-1, CD4, CD8, CD204, and αSMA. If the proportion of positively stained tumor cells was greater than or equal to 5%, the tumor was considered to show FRα expression; if the H-score was more than or equal to 60, the tumor was considered to show high FRα expression. ResultsOverall, 466 TMA cores created from 233 LADC patients were evaluated: FRα-positive expression (FRα-pos)/negative (FRα-neg), 222/11; FRα high expression (FRα-HE)/low (FRα-LE), 190/43. AnEGFR mutation was present in 53.2 % of the patients. The median H-score of FRα expression, FRα-pos rate, and FRα-HE rate for EGFR mutation/wild type were 159/104 (p = 0.0002), 97.6/92.7 % (p = 0.0773), and 88.7/73.4 % (p = 0.0026), respectively. The H-scores for FRα had mild correlations with the proportion of tumor cells with positive staining for PD-L1 (r=-0.2557, p < 0.0001), the number of CD8-positive cells per square millimeter (r=-0.1767, p = 0.0069), and the area with positive staining for αSMA (r = 0.2049, p = 0.0017). No correlations were seen between FRα expression and other cancer-immunity markers. ConclusionTumor FRα expression was significantly higher in LADCs withEGFR mutation than in those with wild-type EGFR. This study suggested that FRα expression was related to cancer and microenvironment-immunity markers such as PD-L1 expression, CD8 cells, and αSMA.

PD-L1 diagnostics in the neoadjuvant setting: implications of intratumoral heterogeneity of PD-L1 expression in triple negative breast cancer for assessment in small biopsies.

PD-L1 expression is a predictive biomarker for anti-PD-L1 immunotherapy in triple negative breast cancer (TNBC). In the neoadjuvant setting, immunohistochemical (IHC) evaluation of PD-L1 expression can only be performed on small tissue biopsies. In our study we investigated heterogeneity of PD-L1 expression in TNBC, and how reliably PD-L1 expression in small tissue samples reflects PD-L1 expression in larger tumor sections in TNBC. Tissue microarrays (TMAs) were constructed from surgical specimens of 110 patients with TNBC. TMAs contained 4 cores (1mm in diameter) per patient. To evaluate PD-L1 expression, TMAs were stained with PD-L1 IHC 22C3 PharmDx. Single-core PD-L1 expression was compared to overall PD-L1 expression of each patient's tumor, to ascertain how often small samples of tumor tissue show the same PD-L1 expression as larger tumor samples. Our study found substantial heterogeneity of PD-L1 expression between different TMA cores from the same patient. Heterogeneity was greater in immune cells (ICs) than in tumor cells, in large part due to the uneven distribution of ICs in the tumor. For IC PD-L1 expression, we found that sensitivity can be as low as 0.81 for detecting PD-L1 expression at the 1% threshold most commonly used in breast cancer. Negative predictive value for ICs was 0.7. There is substantial heterogeneity of PD-L1 expression between small tissue samples from the same TNBC tumor, especially for IC expression. This poses challenges for evaluation of PD-L1 expression in the neoadjuvant setting. Negative biopsies should prompt further investigation, and multiple biopsies might be necessary.

Prognostic impact of stromal and intratumoral CD3, CD8 and FOXP3 in adjuvantly treated breast cancer: do they add information over stromal tumor-infiltrating lymphocyte density?

Tumor-infiltrating lymphocytes (TILs) and their subsets contribute to breast cancer prognosis. We investigated the prognostic impact of CD3+, CD8+ and FOXP3+ TILs in patients with early intermediate/high-risk breast cancer treated with adjuvant anthracycline-based chemotherapy within two randomized trials conducted by our Group. We examined 1011 patients (median follow-up 130.9months) and their tumors for total, stromal (s) and intratumoral (i) CD3, CD8 and FOXP3 lymphocyte density (counts/mm2) on tissue-microarray cores by immunohistochemistry. Morphological sTIL density on whole H&E-stained sections was also evaluated. The majority of TILs were CD3+. Total CD3 and CD8, sCD3 and sCD8, iCD3 and iCD8, sFOXP3 and iFOXP3 were strongly correlated (Spearman's rho values > 0.6). High individual lymphocytic subsets and sTIL density were strongly associated with high tumor grade, higher proliferation and HER2-positive and triple-negative tumors (all p values < 0.001). Higher sTIL density (10% increments), high density of almost each individual marker and all-high profiles conferred favorable prognosis. However, when adjusted for sTIL density, stromal and intratumoral lymphocytic subsets lost their prognostic significance, while higher sTIL density conferred up to 15% lower risk for relapse. Independently of sTIL density, higher total CD3+ and CD8+ TILs conferred 35% and 28% lower risk for relapse, respectively. Stromal and intratumoral CD3+, CD8+ and FOXP3+ TIL density do not seem to add prognostic information over the morphologically assessed sTIL density, which is worth introducing in routine histology reports.

Ki-67 Proliferation Index in Breast Cancer as a Function of Assessment Method: A NordiQC Experience.

Immunohistochemical staining for Ki-67 is used to calculate a Ki-67 proliferation index (PI) that carries prognostic and predictive information in various cancers including breast carcinomas. Studies have documented challenges for observers to reproducibly estimate the Ki-67 PI. At present, no international consensus exists concerning scoring method (eg, hotspots vs. overall average, digital vs. manual counting) or even the definition of a Ki-67-positive cell. To clarify the approach to Ki-67 scoring and evaluation of the interobserver agreement among participants in the Nordic Immunohistochemical Quality Control (NordiQC) Breast Cancer Module, a study was set up on the basis of an online web module containing 15 digitized tissue microarray cores of breast carcinomas stained for Ki-67 in the NordiQC reference laboratory. All participants were invited to attend the study. In addition to Ki-67 scoring, they were asked to disclose their preferred method for Ki-67 estimation and their job title. For comparison, slides were analyzed using a Digital Image Analysis algorithm based on Virtual Double Staining. In total, 199 participants enrolled for the study. Overall, there was a good correlation in Ki-67 PIs among the participants, although results for some cores varied significantly. However, when applying a cutoff of 20%, a relatively low κ value of 0.52 was observed. Participants scoring in hotspots reported higher Ki-67 PIs than participants estimating an overall average, and, not surprisingly, participants who considered weak Ki-67 nuclear staining positive obtained higher Ki-67 PIs than those who did not. Ki-67 PI was not correlated to job title. The Virtual Double Staining algorithm obtained Ki-67 values close to the mean value of the human observers. Our study underlines the need for international standardization and guidelines in estimation of Ki-67 PI. Digital Image Analysis may be a useful tool in this process.

Risk Stratification of Prostate Cancer Through Quantitative Assessment of PTEN Loss (qPTEN).

Phosphatase and tensin homolog (PTEN) loss has long been associated with adverse findings in early prostate cancer. Studies to date have yet to employ quantitative methods (qPTEN) for measuring of prognostically relevant amounts of PTEN loss in postsurgical settings and demonstrate its clinical application. PTEN protein levels were measured by immunohistochemistry in radical prostatectomy samples from training (n = 410) and validation (n = 272) cohorts. PTEN loss was quantified per cancer cell and per tissue microarray core. Thresholds for identifying clinically relevant PTEN loss were determined using log-rank statistics in the training cohort. Univariate (Kaplan-Meier) and multivariate (Cox proportional hazards) analyses on various subpopulations were performed to assess biochemical recurrence-free survival (BRFS) and were independently validated. All statistical tests were two-sided. PTEN loss in more than 65% cancer cells was most clinically relevant and had statistically significant association with reduced BRFS in training (hazard ratio [HR] = 2.48, 95% confidence interval [CI] = 1.59 to 3.87; P < .001) and validation cohorts (HR = 4.22, 95% CI = 2.01 to 8.83; P < .001). The qPTEN scoring method identified patients who recurred within 5.4 years after surgery (P < .001). In men with favorable risk of biochemical recurrence (Cancer of the Prostate Risk Assessment - Postsurgical scores <5 and no adverse pathological features), qPTEN identified a subset of patients with shorter BRFS (HR = 5.52, 95% CI = 2.36 to 12.90; P < .001) who may be considered for intensified monitoring and/or adjuvant therapy. Compared with previous qualitative approaches, qPTEN improves risk stratification of postradical prostatectomy patients and may be considered as a complementary tool to guide disease management after surgery.

Deep learning-based approach for automated assessment of PTEN status.

294 Background: PTEN loss is associated with adverse outcomes in prostate cancer and has the potential to be clinically implemented as a prognostic biomarker. Deep learning algorithms applied to digital pathology can provide automated and objective assessment of biomarkers. The objective of this work was to develop an artificial intelligence (AI) system for automated detection and localization of PTEN loss in prostate cancer samples. Methods: Immunohistochemistry (IHC) was used to measure PTEN protein levels on prostate tissue microarrays (TMA) from two institutions (in-house n=272 and external n=125 patients). TMA cores were visually scored for PTEN loss by pathologists and, if present, spatially annotated. In-house cohort (N=1239 cores) were divided into 70/20/10 training/validation/testing sets. Two algorithms were developed: a) Class I=core-based, to label each core for biomarker status and b) Class II=pixel-based, to spatially distinguish areas of PTEN loss within each core. ResNet101 architecture was used to train a multi-resolution ensemble of classifiers at 5x, 10x, and 20x for Class I task and a single classifier at simulated 40x for Class II segmentation. Results: For Class I algorithm, accuracy of PTEN status was 88.3% and 93.4% in validation and testing cohorts, respectively (Table). AI-based probability of PTEN loss was higher in cores with complete loss vs partial loss. Accuracy was improved to 90.7% in validation and 93.5% in test cohorts using the Class II region-based algorithm, with median dice scores 0.833 and 0.831, respectively. Direct application to external set demonstrated a high false positive rate. Loading trained model and conservatively re-training (“fine-tuning”) on 48/320 external cohort cores improved accuracy to 93.4%. Conclusions: Results demonstrate feasibility and robustness for fully automated detection and localization of PTEN loss in prostate cancer tissue samples and possibility for time/cost-effectiveness of sample processing/scoring in research and clinical laboratories.[Table: see text]

Abstract P2-10-02: Racial differences in infiltration of CD8+ T-cells in breast tumors of Black and White women

Abstract Background: Racial disparities in breast cancer outcome continues to be a major health care challenge. The reasons underlying this disparity are multifactorial with a recent focus on the tumor microenvironment. The characterization of infiltrating immune cell populations in the tumor microenvironment are lacking in Black breast cancer patients. To address this research gap, we employed immunohistochemical (IHC) staining and quantitative digital imaging to assess CD8+ T-cells in breast tumor samples from the Women’s Circle of Health Study (WCHS), a population-based case-control study of breast cancer in Black and White women. Our aim was to characterize and compare the density, localization and distribution of CD8+ T cells, and explore their prognostic value in each racial group. Methods: Tumor-infiltrating CD8+ lymphocytes were assessed by IHC staining of tissue microarray (TMA) cores from 736 breast cancer patients, including 597 Blacks and 139 Whites. The Aperio platform was used for quantitative image analysis of TMA cores. Racial differences in demographic and clinical characteristics were evaluated using the Mann-Whitney U and Fisher’s exact tests. Overall (OS) and breast cancer-specific (DSS) survival were summarized by race using the Kaplan-Meier method and compared using the log-rank test. The associations between demographic/clinical factors and CD8 expression were evaluated using a general linear model (GLM). Multivariable Cox regression models were used to evaluate associations between survival outcomes and both race and CD8 expression, while adjusting for age. Results: Black women had a higher percentage of high-grade tumors in addition to higher prevalence of ER-negative and triple negative tumors than white women. There was a statistically significant difference in OS (p=0.043), showing worse outcomes among Black patients. Black patients had significantly higher CD8+ expression compared to White patients, with mean values of 756.2/mm2 and 292.4/mm2 respectively (p&amp;lt;0.001). This was consistent across all subtypes, with the highest CD8+ expression seen in Black patients with triple negative breast cancer (p&amp;lt;0.001). Higher CD8+ expression was significantly correlated with higher tumor grade and higher Ki67 scores (p&amp;lt;0.001). There was significantly higher expression of CD8+ T-cells in Stage II disease in comparison to stages I, III and IV in both races (p =0.01). Furthermore, there was a significant inverse relationship between age and CD8+ expression (p=0.002). Neoadjuvant chemotherapy did not seem to have a significant effect on CD8+ T-Cell expression (p=0.46). No significant associations were observed between CD8 expression in tertiles and OS or DSS overall or within each cancer subtype. Further analyses are being conducted to assess CD8+ T cells in the stromal and tumor segments. Conclusions: We observed a stronger presence of CD8+ T cells in tumor microenvironment from Black breast patients, suggesting the existence of distinct tumor immune responses in this population. Our current data do not support that CD8+ T cells contribute to breast cancer survival disparities given the lack of prognostic significance of CD8 expression in this sample. CD8+ T cells may become less cytotoxic towards tumor cells as a result of immunosuppression or exhaustion; therefore, in-depth immuno-profiling of the versatile immune cell subsets and their qualities of breast tumor microenvironment in Black patients is warranted to understand their roles in breast cancer racial disparities. Citation Format: Yara Abdou, Song Yao, Kristopher Attwood, Gary Zirpoli, Wiam Bshara, Christine Ambrosone, Angela Omilian. Racial differences in infiltration of CD8+ T-cells in breast tumors of Black and White women [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-02.

Abstract P2-10-18: Deciphering racial disparities in breast cancer collagen reorganization by targeted extracellular matrix proteomics

Abstract Although European American women have a higher incidence of breast cancer, African American women have higher mortality rates with increased occurrence of lethal cancers at a younger age. Breast density, characterized by increases in stroma, is a risk factor for breast cancer and African American women have significantly greater odds of high breast density compared to European American women. Genomic profiling of breast cancer by ancestry shows that stromal collagen type genes vary based on African and European ancestry and correlate to differences in breast cancer progression and survival. Contemporary scientific literature describes breast cancer progression as being linked to a “collagen switch” whereby collagen fibers surrounding the tumor are re-organized during later tumor growth to facilitate metastatic spread of cancer activated fibroblasts. However, mechanisms facilitating the “collagen switch” remain mostly unknown, especially at a translational level. Additionally, collagen re-organization has not yet been evaluated for contributions to racial disparities in breast cancer. Our novel extracellular matrix proteomic studies on 17 patient lumpectomies depict that very specific sites on collagen protein types in breast tumor are post-translationally regulated by hydroxylation of proline (HYP) dependent on race (7 African American, 10 European American; no significant age or receptor status difference). By proteomic sequencing, distinct peptide sequences of collagen 1A1, collagen 1A2, and collagen 3A1 are modified by HYP and are significantly regulated when measured in African American versus European American breast tumors. From 16 collagen type proteins, 143 collagen peptides from all breast tumors were identified with HYP modifications (site probability ≥0.95). A total of 16% of the HYP peptides were unique to African American breast tumors. Imaging mass spectrometry that targets collagens reported that specific peptides sequences showed increased hydroxylation of proline in tumors compared to normal adjacent tissue. Interestingly, but not unexpected, translational and post-translational regulation did not always correlate with transcriptional regulation. Investigation on over 300 tissue microarray cores of breast tumor by second harmonic generation microscopy demonstrated significant ancestry-defined regulation of collagen fibers. For example, compared to breast tumor tissue cores of European American ancestry, African American breast tumor tissue cancer cores showed significant overall increases in collagen fibril length with decreased collagen fibril straightness (two-tailed student’s t-test p-value &amp;lt;0.05). Imaging mass spectrometry that targets collagens done on the identical set of 300 ancestry-defined tissue microarray cores supports that ancestry of breast tumor correlates with site specific collagen modification by hydroxylation of prolines. For instance, COL3A1 peptide GPAGIPx GFPx shows a nearly 3-fold increase in African American breast tumors compared to European breast tumors (Mann-Whitney p-value ≤0.02; area under the receiver operating curve 0.81, p-value ≤0.0001; HYP site probability of 1.00 for each proline designated Px). Since HYP stabilizes collagen triple helices, we hypothesize that HYP alteration at specific sites in collagen protein types from African American breast tumors may reflect a change in collagen flexibility that contributes to an earlier metastatic collagen switch than in European American breast tumors. Current work determines ancestry-related changes in collagen fibers per breast cancer type and per normal adjacent tissue. To summarize, we provide the first evidence that post-translational regulation of collagen types may contribute to racial disparities in breast cancer. Citation Format: Peggi M Angel, Janet Saunders, Heather Jensen-Smith, Evelyn Bruner, Marvella E. Ford, Savanna Berkhiser, Baylye Boxall, Jennifer Bethard, Lauren E. Ball, Elizabeth S. Yeh, Michael A. Hollingsworth, Anand S. Mehta, Jeffrey R. Marks, Harikrishna Nakshatri, Richard R. Drake. Deciphering racial disparities in breast cancer collagen reorganization by targeted extracellular matrix proteomics [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-18.

A de-waxing methodology for scanning probe microscopy.

A de-waxing protocol that successfully removes paraffin from tissue microarray (TMA) cores of fixed tissue obtained from oral cancer is described. The success of the protocol is demonstrated by the comparison of Fourier transform infrared (FTIR) results obtained on paraffin-embedded and de-waxed tissue and the absence of any significant correlations between infrared scanning near-field optical microscopy (SNOM) images of de-waxed tissue obtained at the three main paraffin IR peaks. The success of the protocol in removing paraffin from tissue is also demonstrated by images obtained with scanning electron microscopy (SEM) and by energy dispersive spectra (EDS) of a de-waxed CaF2 disc which shows no significant contribution from carbon. The FTIR spectra of the de-waxed TMA core overlaps that obtained from OE19 oesophageal cancer cells which had never been exposed to paraffin.

Antibody selection influences the detection of AR-V7 in primary prostate cancer

BackgroundThe androgen receptor (AR) splice variant V7 (AR-V7) is an emerging marker to aid clinical decision-making in patients with castration-resistant prostate cancer (CRPC). A number of studies have shown that a subset of patients also express AR-V7 in the primary tumor. These findings have recently been challenged by a study showing that AR-V7 becomes only detectable in CRPC but is virtually absent in castration-naïve prostate cancer. MethodsHerein, we directly compare the two relevant antibodies used for the immunodetection of AR-V7 in the conflicting studies (clones AG10008 and RM7) in a predominantly high-risk prostate cancer patient cohort with primary tumor specimens assembled in a tissue microarray (TMA). ResultsThe overall rate of AR-V7 positive TMA cores was comparable (AG10008, 24.9%; RM7, 21%). However, the percentage agreement of identical staining intensities of positive cores was only 7%. In contrast, the percentage agreement of negative cores was 62.8%. In approximately 30% of the cores, the antibodies produced discordant staining intensities. Only one of the two antibody stainings (AG10008) conveyed prognostic information and was associated with a shorter progression-free patient survival. ConclusionsOur study underscores that nuclear AR-V7 expression can be detected in primary prostate cancer prior to long-term androgen deprivation and castration resistance. There are staining differences between the two antibodies in tumor tissue, for which we currently have no explanation. Clearly, improvements in the detection of functional AR-V7 in prostate cancer are urgently needed.

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions. We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores. In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant. HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.

Tumor Infiltrating Lymphocytes and CD8+ T Cell Subsets as Prognostic Markers in Patients with Surgically Treated Laryngeal Squamous Cell Carcinoma.

To evaluate the prognostic significance of tumor infiltrating lymphocytes (TILs) and of CD8+ T-cell subsets in patients with surgically treated laryngeal squamous cell carcinoma (LSCC), LSCC from 283 patients were examined. TIL density was morphologically assessed on whole sections. CD8+ cell counts/mm2 were evaluated on multiple tissue microarray cores per tumor (median counts for high/low CD8+/mm2). TIL density and CD8+ counts weakly correlated with each other (Spearman's rho = 0.348). Heterogeneous CD8+ counts/mm2 were demonstrated in 28% of the tumors. In univariate analysis, a significant interaction was observed between CD8 expression and nodal status with respect to outcome; in node-positive patients, those with high CD8+ tumors had 77% lower risk of relapse (interaction p < 0.001) and 74% lower risk for death (interaction p = 0.002) compared to patients with low CD8+ tumors. In multivariate analysis, higher TIL density independently conferred lower risk for relapse in the entire cohort (HR 0.87; 95% CI 0.77-0.98; Wald's p = 0.017) and in node-positive patients (HR 0.41; 95% CI 0.23-0.75; p = 0.003) and, similarly, for death (p = 0.025 and p = 0.003, respectively). High CD8+ was not a significant independent prognostic marker in any analysis setting. The assessment of CD8+ infiltrates does not seem to offer additional prognostic information over the morphologically assessed TIL density. It also appears that the favorable prognostic impact of higher TIL density and CD8+ infiltrates mostly concerns node-positive but not node-negative disease. If validated in larger node-positive cohorts, these findings are worth considering for the diagnostic development of immune cell infiltrates in LSCC.

Programmed death-ligand 1 expression influenced by tissue sample size. Scoring based on tissue microarrays' and cross-validation with resections, in patients with, stage I-III, non-small cell lung carcinoma of the European Thoracic Oncology Platform Lungscape cohort.

PD-L1, as assessed by immunohistochemistry, is a predictive biomarker for immuno-oncology treatment in lung cancer. Different scoring methods have been used to assess its status, resulting in a wide range of positivity rates. We use the European Thoracic Oncology Platform Lungscape non-small cell lung carcinoma cohort to explore this issue. PD-L1 expression was assessed via immunohistochemistry on tissue microarrays (up to four cores per case), using the DAKO 28-8 immunohistochemistry assay, following a two-round external quality assessment procedure. All samples were analyzed under the same protocol. Cross-validation of scoring between tissue microarray and whole sections was performed in 10% randomly selected samples. Cutoff points considered: ≥1, 50 (primarily), and 25%. At the two external quality assessment rounds, tissue microarray scoring agreement rates between pathologists were: 73% and 81%. There were 2008 cases with valid immunohistochemistry tissue microarray results (50% all cores evaluable). Concordant cases at 1, 25, and 50% were: 85, 91, and 93%. Tissue microarray core results were identical for 70% of cases. Sensitivity of the tissue microarray method for 1, 25, and 50% was: 80, 78, and 79% (specificity: 90, 95, 98%). Complete agreement between tissue microarrays and whole sections was achieved for 60% of the cases. Highest sensitivity rates for 1% and 50% cutoffs were detected for higher number of cores. Underestimation of PD-L1 expression on small samples is more common than overestimation. We demonstrated that classification of PD-L1 on small biopsy samples does not represent the overall expression of PD-L1 in all non-small cell cancer carcinoma cases, although the majority of cases are 'correctly' classified. In future studies, sampling more and larger biopsies, recording the biopsy size and tumor load may permit further refinement, increasing predictive accuracy.

Highly Multiplexed Single Cell Spatial Analysis of the Tumor Microenvironment in Lymphoma Predicts Clinical Outcomes

Background Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma. Although a majority of patients are cured with standard chemo-immunotherapy, up to 40% of DLBCL patients have refractory disease or develop relapse following R-CHOP regimen, warranting development of novel, more effective therapeutic strategies for this cohort[1]. The composition of immune cells in the tumor microenvironment (TME) and tumor PD-L1 expression have been reported to predict DLBCL outcomes, however PD1 inhibitors demonstrate response rates of less than 10%.[2-5] We hypothesize that a better characterization of spatial architecture of the tumour microenvironment (TME) in lymphoma will help explain why DLBCL has poor responses to PD1 inhibitors and guide future targeted immunotherapies for these patients. Methods Here we characterized the TME in DLBCL using imaging mass cytometry (IMC), which allows high-dimensional, single-cell and spatial analysis of FFPE tissues at sub-cellular resolution [6]. Using a panel of 32 antibodies, IMC was performed 41 tissue microarray cores from 33 DLBCL cases. IMC images were analyzed for relevant immunophenotypes, the spatial architecture of those phenotypes and compared to clinical outcomes to identify immune contexture based biomarkers. Results Phenograph was used to cluster tumor and immune cells based on phenotype. Immune cells represented 33% of the cells broken down to CD4 (36%), CD8 (30%), macrophages (26%) and TREG(8%) (Figure A).Immune cell infiltration in individual tumor samples ranged from 7% to 75% with marked heterogeneity between samples. Analysis of immune marker expression on tumor cells identified co-expression of PD-L1/CCR4/TIM3 to be highly prognostic for overall survival (p=0.003, Figure B-C) To characterize the patterns of spatial interaction in the TME, we developed an unsupervised multivariate model to construct spatial meta-clusters based on average distances from CD8 to the centroids of 5 nearest endothelial cells, TREG, CD4 T cells, macrophages, and tumor cells (Figure D). Spatial analysis revealed 11 meta-clusters for CD8 T cell interactions (Figure E). Each CD8 spatial interaction pattern is distinctive with case to case heterogeneity (Figures F). Risk assessment analyses of spatial clusters 1, 2 and 4 ("hazardous") had almost 3 times higher odds of being identified in refractory cases compared to clusters 3, 5 and 6 ("protective") (Figure G). In the "protective" spatial neighborhoods, we observed the presence of activated CD8, Th1-like CD4, and less suppressive TREGphenotypes, with opposite in "hazardous" areas (Figures H). TIM-3 expression was high both on T cells and tumor cells in the "hazardous" neighborhoods. Finally, we show that sub-setting our analysis of CD8 phenotypes based on their spatial location to other cells improved our ability to predict overall survival in the cohort. Conclusion These results are the first to demonstrate that spatial profiling of immune architecture in DLBCL is associated with clinical outcomes, and that spatial analysis of immune cells should be explored as a potential biomarker for patients treated with immunotherapies.

The adequacy of tissue microarrays in the assessment of inter- and intra-tumoural heterogeneity of infiltrating lymphocyte burden in leiomyosarcoma

The characterisation and clinical relevance of tumour-infiltrating lymphocytes (TILs) in leiomyosarcoma (LMS), a subtype of soft tissue sarcoma that exhibits histological heterogeneity, is not established. The use of tissue microarrays (TMA) in studies that profile TIL burden is attractive but given the potential for intra-tumoural heterogeneity to introduce sampling errors, the adequacy of this approach is undetermined. In this study, we assessed the histological inter- and intra-tumoural heterogeneity in TIL burden within a retrospective cohort of primary LMS specimens. Using a virtual TMA approach, we also analysed the optimal number of TMA cores required to provide an accurate representation of TIL burden in a full tissue section. We establish that LMS have generally low and spatially homogenous TIL burdens, although a small proportion exhibit higher levels and more heterogeneous distribution of TILs. We show that a conventional and practical number (e.g. ≤3) of TMA cores is adequate for correct ordinal categorisation of tumours with high or low TIL burden, but that many more cores (≥11) are required to accurately estimate absolute TIL numbers. Our findings provide a benchmark for the design of future studies aiming to define the clinical relevance of the immune microenvironments of LMS and other sarcoma subtypes.

S100A8 Expression May Have a Prognostic Value in CCRCC Reflecting TNM Staging and Fuhrman Nuclear Grade.

S100A8 is a chemoattractant known to be associated with metastatic niche formation. Herein, we evaluated the prognostic value of S100A8 in patients with clear cell renal cell carcinoma (CCRCC). A total of 152 CCRCC patients who have undergone nephrectomy were enrolled. The expression of S100A8 was assessed immunohistochemically using tissue microarray (TMA) blocks of CCRCC. Using statistical analysis, the relationship between S100A8 expression and clinicopathological factors was evaluated. Among 152 TMA cores, 21 (6.9%) showed higher S100A8 expression. S100A8 expression was significantly increased in cores of patients with higher T stage (≥2, p<0.001) and higher Fuhrman nuclear grade (≥3, p<0.001). Multivariate analysis confirmed that high expression of S100A8 was significantly correlated to poor disease-free survival (hazard ratio, 2.601; 95% confidence interval (CI), 1.020-6.628; p-value=0.045). S100A8 expression may have a prognostic value in CCRCC reflecting TNM staging and Fuhrman nuclear grade.