Immuno-oncology Biomarker Research Articles

Gut Microbiota-Related Biomarkers in Immuno-Oncology.

Carcinogenesis is associated with the emergence of protracted intestinal dysbiosis and metabolic changes. Increasing evidence shows that gut microbiota-related biomarkers and microbiota-centered interventions are promising strategies to overcome resistance to immunotherapy. However, current standard methods for evaluating gut microbiota composition are cost- and time-consuming. The development of routine diagnostic tools for intestinal barrier alterations and dysbiosis constitutes a critical unmet medical need that can guide routine treatment and microbiota-centered intervention decisions in patients with cancer. In this review, we explore the influence of gut microbiota on cancer immunotherapy and highlight gut-associated biomarkers that have the potential to be transformed into simple diagnostic tools, thus guiding standard treatment decisions in the field of immuno-oncology. Mechanistic insights toward leveraging the complex relationship between cancer immunosurveillance, gut microbiota, and metabolism open exciting opportunities for developing novel biomarkers in immuno-oncology.

Tumor-Infiltrating Lymphocytes in Patients With Stage I Triple-Negative Breast Cancer Untreated With Chemotherapy

The absolute benefit of chemotherapy for all patients with stage I triple-negative breast cancer (TNBC) is unclear, and biomarkers are not currently available for selecting patients with an excellent outcome for whom neoadjuvant or adjuvant chemotherapy may have negligible benefit. High levels of stromal tumor-infiltrating lymphocytes (sTILs) are associated with favorable survival in TNBC, but data solely in stage I TNBC are lacking. To examine the outcomes of patients of all ages with stage I TNBC solely and who received neither neoadjuvant nor adjuvant chemotherapy, according to centrally reviewed sTIL levels at prespecified cutoffs. This cohort study used the Netherlands Cancer Registry to identify patients diagnosed with stage I TNBC between January 1, 2005, and December 31, 2015, who were not treated with chemotherapy. Only patients who did not receive neoadjuvant and/or adjuvant chemotherapy were selected. The clinical data were matched with their corresponding pathology data provided by the Dutch Pathology Registry. Data analysis was performed between February and October 2023. The primary end point was breast cancer-specific survival (BCSS) at 5, 10, and 15 years for the prespecified sTIL level cutoffs of 30%, 50%, and 75%. Hematoxylin and eosin-stained slides were used for central review of histologic subtype, grade, and lymphovascular invasion. The International Immuno-Oncology Biomarker Working Group guidelines were used to score the sTIL levels; these levels were determined for 1041 patients. Of a total of 4511 females with stage I TNBC, patients who were not treated with chemotherapy were selected and tissue blocks requested; sTILs were scored in 1041 patients (mean [SD] age at diagnosis, 64.4 [11.1] years, median follow-up 11.4 [95% CI, 10.9-11.9] years) who were included in the analyses.. Most tumors (952 [91.5%]) were invasive carcinomas of nonspecial histologic subtype. Most patients (548 [52.6%]) had pT1cN0 tumors. Median (range) sTIL level was 5% (1%-99%). A total of 775 patients (74.4%) had sTIL levels below 30%, 266 (25.6%) had 30% or greater, 203 (19.5%) had 50% or greater, and 141 (13.5%) had 75% or greater. Patients with pT1abN0 tumors had a more favorable outcome vs patients with pT1cN0 tumors, with a 10-year BCSS of 92% (95% CI, 89%-94%) vs 86% (95% CI, 82%-89%). In the overall cohort, sTIL levels of at least 30% were associated with better BCSS compared with sTIL levels less than 30% (96% and 87%, respectively; hazard ratio [HR], 0.45; 95% CI, 0.26-0.77). High sTIL levels of 50% or greater were associated with a better outcome than low sTIL levels of less than 50% (HR, 0.27; 95% CI, 0.10-0.74) in patients with pT1C tumors, with a 10-year BCSS of 95% increasing to 98% with sTIL levels of 75% or greater. Results of this study showed that patients with stage I TNBC and high level of sTILs who did not receive neoadjuvant or adjuvant chemotherapy had excellent 10-year BCSS. The findings further support the role of sTILs as integral biomarkers in prospective clinical trials of therapy optimization for this patient population.

Genomic and Immune Landscape Comparison of MET Exon 14 Skipping and MET-Amplified Non-small Cell Lung Cancer

BackgroundMutation or amplification of the mesenchymal-epithelial transition (MET) tyrosine kinase receptor causes dysregulation of receptor function and stimulates tumor growth in non-small cell lung cancer (NSCLC) with the most common mutation being MET exon 14 (METex14). We sought to compare the genomic and immune landscape of MET-altered NSCLC with MET wild-type NSCLC. Methods18,047 NSCLC tumors were sequenced with Tempus xT assay. Tumors were categorized based on MET exon 14 (METex14) mutations; low MET amplification defined as a copy number gain (CNG) 6-9, high MET amplification defined as CNG ≥ 10, and MET other type mutations. Immuno-oncology (IO) biomarkers and the frequency of other somatic gene alterations were compared across MET-altered and MET wild-type groups. Results276 (1.53%) METex14, 138 (0.76%) high METamp, 63 (0.35%) low METamp, 27 (0.15%) MET other, and 17,543 (97%) MET wild-type were identified. Patients with any MET mutation including METex14 were older, while patients with METex14 were more frequently female and nonsmokers. MET gene expression was highest in METamp tumors. PD-L1 positivity rates were higher in MET-altered groups than MET wild-type. METex14 exhibited the lowest tumor mutational burden (TMB) and lowest neoantigen tumor burden (NTB). METamp exhibited the lowest proportion of CD4 T cells and the highest proportion of NK cells. There were significant differences in co-alterations between METamp and METex14. ConclusionsMETex14 tumors exhibited differences in IO biomarkers and the somatic landscape compared to non-METex14 NSCLC tumors. Variations in immune profiles can affect immunotherapy selection in MET-altered NSCLC and require further exploration.

Abstract 3652: Spatial transcriptomic study of the tumor microenvironment in HNSCC

Abstract Background: The complex and dynamic nature of the tumor-immune microenvironment (TME) presents challenges for identification of robust and predictive biomarkers in immuno-oncology (IO). Standard multiplex immunohistochemistry (mIHC) or multiplex immuno-fluorescent assays (mIF) allow for the phenotyping on the cellular level but are limited by the number of markers available and the detection systems. Gene expression or next generation sequencing (NGS) platforms provide high-plex bulk data sets about the TME, but the spatial context of the tumor and immune cell interactions is lost. The NanoString GeoMx® Digital Spatial Profiler (DSP) combines spatial context, utilizing fluorescent morphological markers, with molecular profiling capabilities. This combination allows for the quantitative analysis of high-plex analyte abundance which can be traced back to a region of interest within a sample, providing biological inference in the region of interest. Methods: Formalin-fixed paraffin-embedded (FFPE) specimens from HNSCC patients were cut in 5µm sections for all analyses. Whole section tissue analysis was previously performed utilizing the NanoString nCounter® PanCancer IO 360™ Panel. Tumor inflammation signatures (TIS), an 18-gene signature measuring the adaptive immune response within tumors, was generated for each specimen and categorized each as immune-hot or immune-cold based on predefined parameters. Four specimens were selected based on their TIS score and two sets of cut sections were processed by either Labcorp lab in Morrisville, NC or Nanostring lab in Seattle, WA for precision evaluation, using the GeoMx Human Whole Transcriptome Atlas (WTA) panel (18,000 genes) with the NanoString GeoMx digital spatial profiling technology. The TME regions of interest (ROI) were identified using a set of morphology markers consisting of panCK, CD45 and Syto13; 12 ROIs were selected from each sectioned tumor material. The same ROIs were selected at the two testing sites with matching tissue location and morphology characters. Results: GeoMx WTA panel provided an unbiased view of 18,000 protein-coding genes at specific TME regions. These counts were successfully mapped to the 12 ROIs on the tissue. A pseudo-TIS score was generated using the same 18 gene signature from the WTA panel for each ROI. The pseudo-TIS scores from ROIs from the four specimens showed consistency with the specimen-wise TIS score, yet variations were observed across different TME/ROI within each specimen. Whole transcriptome expression results showed high correlation between the two testing sites, providing confidence in the reproducibility of the technology. High resolution fluorescent staining images were able to be fed to downstream quantitative digital analysis to generate complementary spatial data. Citation Format: Caitlin Schroyer, Shanshan Zhou. Spatial transcriptomic study of the tumor microenvironment in HNSCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3652.

Abstract 6886: Orion™: 17-plex single-step stain and imaging of normal lung section adjacent to non-small cell lung carcinoma

Abstract Background: The ability to image tissue microenvironments (TME) at high-plex over a whole slide without requiring multiple staining steps allows for unprecedented ability to study tissue architecture and molecular mechanisms of immune and disease processes. Here we investigate a sample of normal lung section adjacent to non-small cell lung carcinoma using whole slide, single-step stain and imaging at single-cell resolution. Methods: These images profiled a whole slide tissue section of normal lung section adjacent to non-small cell lung carcinoma, stained with a 17-plex immuno-oncology biomarker panel. In this profile, we designed a high-plex panel of 17 biomarkers where the tissue autofluorescence was imaged and isolated as an additional fluorescence channel. All markers were stained in a single staining procedure and imaged in a single scan. Whole slide spatial staining and imaging was conducted on the Orion spatial biology platform. The full protocol is quick and simple, using standard histology tools: •Mount sections on glass slides•De-paraffinize and perform antigen retrieval•Quench autofluorescence•Stain slides with a panel of ArgoFluor™ conjugated antibodies•Coverslip with ArgoFluor Mounting Medium and cure overnight•Image whole slides at 20X magnification using the Orion instrument•Process to ome.TIFF and analyze. Results: Data revealed intact normal lung alveolar architecture, with scattered immune cell infiltrates. Multiplexed imaging revealed epithelial cells, which make up alveoli, and endothelial vasculature as well as immune cells infiltrates in the alveolar space. Various immune cell populations were observed to be present (T cells, B cells, macrophages) and immune cell activation could be distinguished using PCNA and/or Ki-67 markers. Various T cell subsets could also be identified among the infiltrate using markers for CD4, CD8 and T-regulatory marker FOXP3. Through the use of multiplex staining, immune cell activity could also be characterized with respect to bronchiolar, artery, and capillary tissue architecture. Conclusions: High-quality subcellular imaging of TME can lead to greater spatial investigation and more in-depth understanding of immune function in normal and diseased tissue. Here, multiplexed imaging identified distinct immune cell collections among cancer-adjacent normal lung tissue, providing validation of instrumentation and methods to obtain benchmarks for spatial quantitation of immune cells in control regions adjacent to cancer tissue. Citation Format: Selena Larkin, Tad George, Eric Kaldjian. Orion™: 17-plex single-step stain and imaging of normal lung section adjacent to non-small cell lung carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6886.

Exploration of the relationship between tumor-infiltrating lymphocyte score and histological grade in breast cancer

BackgroundThe histological grade is an important factor in the prognosis of invasive breast cancer and is vital to accurately identify the histological grade and reclassify of Grade2 status in breast cancer patients.MethodsIn this study, data were collected from 556 invasive breast cancer patients, and then randomly divided into training cohort (n = 335) and validation cohort (n = 221). All patients were divided into actual low risk group (Grade1) and high risk group (Grade2/3) based on traditional histological grade, and tumor-infiltrating lymphocyte score (TILs-score) obtained from multiphoton images, and the TILs assessment method proposed by International Immuno-Oncology Biomarker Working Group (TILs-WG) were also used to differentiate between high risk group and low risk group of histological grade in patients with invasive breast cancer. Furthermore, TILs-score was used to reclassify Grade2 (G2) into G2 /Low risk and G2/High risk. The coefficients for each TILs in the training cohort were retrieved using ridge regression and TILs-score was created based on the coefficients of the three kinds of TILs.ResultsStatistical analysis shows that TILs-score is significantly correlated with histological grade, and is an independent predictor of histological grade (odds ratio [OR], 2.548; 95%CI, 1.648–3.941; P < 0.0001), but TILs-WG is not an independent predictive factor for grade (P > 0.05 in the univariate analysis). Moreover, the risk of G2/High risk group is higher than that of G2/Low risk group, and the survival rate of patients with G2/Low risk is similar to that of Grade1, while the survival rate of patients with G2/High risk is even worse than that of patients with G3.ConclusionOur results suggest that TILs-score can be used to predict the histological grade of breast cancer and potentially to guide the therapeutic management of breast cancer patients.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumor-infiltrating lymphocytes in oral cavity squamous cell carcinoma and its association with clinicopathological parameters

BackgroundOral squamous cell carcinoma is one of the most common cancers of the head and neck region. Tumor-infiltrating lymphocytes are naturally occurring mononuclear cells that infiltrate the tumor microenvironment. The aim of the present study is the evaluation of stromal tumor-infiltrating lymphocytes (TILs) in oral squamous cell carcinoma and its association with clinicopathological parameters like age, gender, site, tumor stage, nodal status, grade, lymphovascular and perineural invasion. MaterialsA total of 51 patients of oral cavity squamous cell carcinomas who underwent resection were included in the study. Assessment of the stromal TILs was done on sections stained with Hematoxylin and eosin using the scoring criteria proposed by the International Immuno-Oncology Biomarker Working Group. TILs were assessed in percentages as continuous scores and subsequently categorized into low TILs (<20%) and high TILs (≥20%). The association between TILs and clinicopathological parameters was evaluated using the Fischer exact/Chi-square test. ResultsAmong the 51 cases evaluated in the present study, low and high TILs were found in 25.5% and 74.5% of cases respectively. TILs were found to show a significant association with tumor size and lymphovascular invasion. However, no significant association was found with age, gender, nodal status, grade, perineural invasion, and site in the oral cavity. ConclusionThe evaluation of TILs as proposed by the International Immuno-Oncology Biomarker Working Group is a simple, inexpensive test. Morphological evaluation of TIL can provide valuable prognostic information in oral cavity squamous cell carcinoma cases and can be incorporated as a part of routine histopathological reporting.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Automated Detection and Scoring of Tumor-Infiltrating Lymphocytes in Breast Cancer Histopathology Slides.

Detection of tumor-infiltrating lymphocytes (TILs) in cancer images has gained significant importance as these lymphocytes can be used as a biomarker in cancer detection and treatment procedures. Our goal was to develop and apply a TILs detection tool that utilizes deep learning models, following two sequential steps. First, based on the guidelines from the International Immuno-Oncology Biomarker Working Group (IIOBWG) on Breast Cancer, we labeled 63 large pathology imaging slides and annotated the TILs in the stroma area to create the dataset required for model development. In the second step, various machine learning models were employed and trained to detect the stroma where U-Net deep learning structure was able to achieve 98% accuracy. After detecting the stroma area, a Mask R-CNN model was employed for the TILs detection task. The R-CNN model detected the TILs in various images and was used as the backbone analysis network for the GUI development of the TILs detection tool. This is the first study to combine two deep learning models for TILs detection at the cellular level in breast tumor histopathology slides. Our novel approach can be applied to scoring TILs in large cancer slides. Statistical analysis showed that the output of the implemented approach had 95% concordance with the scores assigned by the pathologists, with a p-value of 0.045 (n = 63). This demonstrated that the results from the developed software were statistically meaningful and highly accurate. The implemented approach in analyzing whole tumor histology slides and the newly developed TILs detection tool can be used for research purposes in biomedical and pathology applications and it can provide researchers and clinicians with the TIL score for various input images. Future research using additional breast cancer slides from various sources for further training and validation of the developed models is necessary for more inclusive, rigorous, and robust clinical applications.

Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers.

e14654 Background: Cytokines have a large impact on the tumor microenvironment by affecting cell growth, survival, inflammation, and differentiation. Understanding the spatial biology within the tumor microenvironment, including the cytokine organization within specific cell types, can lead to better treatment plans for patients. Methods: We developed a hybrid multiplex panel, using RNA in-situ hybridization (ISH) and immunofluorescence (IF) to investigate the spatial biology of the tumor microenvironment. This panel also enabled us to simultaneously detect the RNA of cytokines and protein of specific immuno-oncology (IO) biomarkers. This allows us to visualize spatially, not only the organization of cell types but also to identify the cellular sources of specific cytokines. In this study, we analyzed the tumor microenvironment of samples from non-small cell lung cancer (NSCLC) and breast cancer in two panels for cytokine RNAs and IO protein biomarkers. Panel 1 included TNFa and IL-2 cytokines combined with CD68 and CD163 IO protein biomarkers. Panel 2 consisted of IL-6 and IL-2 cytokines with PAX5 and CD3 IO protein biomarkers. Staining was completed on the Leica Bond RX autostainer, and slides were scanned using the PhenoImager Fusion. Visiopharm software wasused to analyze the tumor microenvironment of tissue samples and localize cytokines in specific cell types. Results: CD163 positive macrophages (M2 phenotype) were seen predominantly within the tumors (NSCLC and breast cancer) whereas CD68 positive macrophages were identified towards the periphery in the non-tumor microenvironment. NSCLC tumor cells showed higher expression levels of IL-2, IL-6 and TNFa compared to breast cancer tumor cells. Predominance of CD3 positive T cells was noted with relative lack of PAX5 positive B cells within both NSCLC and breast cancer tumors. Multiplexing enabled assessment of relative expression levels of IL-2, IL-6 and TNFa in T lymphocytes and macrophages and TNFa in dendritic cells. Conclusions: Our hybrid multiplex panel can provide insights into the visualization of spatial organization of tumor microenvironment. It also enables semi-quantitative assessments for the expression levels of cytokines and their relative expression within tumor and immune cells, thereby helping to correlate response to treatment, especially with checkpoint inhibitors.

Genomic comparison of MET exon 14 skipping and MET amplified non-small cell lung cancer.

8553 Background: In non-small cell lung cancer (NSCLC), the MET tyrosine kinase receptor can be dysregulated by mutations and/or gene amplification. The most common MET mutation is in exon 14 (METex14), leading to impaired receptor degradation and increased MET-mediated signaling causing sustained tumor proliferation. MET amplification also leads to continued MET signaling and oncogenesis and can be a mechanism of resistance to targeted therapy. We sought to compare the genomic landscape of METex14 and high-level MET amplified tumors, both of which can be targeted with tyrosine kinase inhibitors. Methods: We analyzed 18,047 NSCLC tumors (any stage/subtype) sequenced with Tempus xT assay (DNA-seq of 648 genes at 500x coverage, full transcriptome RNA-seq). Tumors were queried for METex14 mutations, high MET amplification (METamp), defined as copy number gain (CNG) ≥10, and other MET mutations (METother). Immuno-oncology (IO) biomarkers were compared across MET-altered and MET wild-type (METwt) groups. The prevalence of somatic gene alterations was compared similarly with the false-discovery rate (FDR) adjustment. Results: A total of 276 (1.53%) METex14, 138 (0.76%) METamp, 27 (0.15%) METother, and 17,606 (97.56%) METwt tumors were identified. Across groups, patients with METex14 were older, more likely to be female, and nonsmokers. METex14 exhibited the lowest tumor mutational burden (TMB) and lowest neoantigen tumor burden (NTB). PD-L1 positivity rates were higher in METex14 tumors compared to METamp and METwt tumors. MET log10 gene expression was highest in METamp. METamp exhibited the lowest proportion of CD4 T cells and the highest proportion of NK cells. Compared to METex14, METamp exhibited increased prevalence of TP53 (83% vs 37%), TFEC (46% vs 1.1%), CFTR (37% vs 1.4%), EGFR (31% vs. 7.6%), WNT2 (11% vs 0.4%), KEAP1 (14% vs 0.7%), and STK11 (8% vs 1.4%), and decreased prevalence of MDM2 (4.3% vs. 14%), and FRS2 (2.9% vs. 12%). Conclusions: In this large population-based analysis of MET-altered NSCLC, METex14 tumors exhibited differences in IO biomarkers and the somatic landscape compared to non-METex14 NSCLC tumors. Variations in immune profiles may affect immunotherapy selection in MET-altered NSCLC and require further exploration. [Table: see text]

Correlation between biomarkers and treatment outcomes in diverse cancers: A meta-analysis of phase I and II immunotherapy clinical trials.

e14638 Background: Many immuno-oncology (IO) trials are conducted without biomarker selection. We performed a meta-analysis of phase I/II clinical trials evaluating immune checkpoint inhibitors (ICIs) to determine the association between biomarkers and clinical outcomes, if any. Methods: We searched PubMed for phase I/II clinical trials of drugs approved by the Food and Drug Administration (labeled, off-label, or combined with investigational ICIs or other treatment modalities) from 2018 to 2020. We compared the objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) between biomarker-positive and biomarker-negative groups, using data from correlative studies. Results: Overall, 174 clinical studies that included 19,178 patients were identified and 131 studies investigated &gt;30 correlative biomarkers, that included PD-L1 expression (≥1%, 111 studies), tumor mutational burden (20 studies), and microsatellite instability/mismatch repair deficiency (10 studies). Overall, 123, 46, and 30 cohorts (drugs, tumor types, or biomarkers) with 11,692, 3,065, and 2,256 patient outcomes for ORR, PFS, and OS, respectively, were analyzed in correlation with biomarkers. Meta-analyses demonstrated that ICIs in patients with biomarker-positive tumors were associated with higher ORR (odds ratio 2.15 [95% CI, 1.79-2.58], p&lt;0.0001); and longer PFS (hazard ratio [HR] 0.55 [95% CI, 0.45-0.67], p&lt;0.0001), and OS (HR 0.65 [95% CI, 0.53-0.80], p&lt;0.0001) compared with those with biomarker-negative tumors. Significance for ORR and PFS was retained in multivariate analysis (p&lt;0.001) (OS, not included owing to the small number of trials reporting OS). Conclusions: Our data suggest that IO biomarkers should be used in patient selection for ICIs. Prospective studies are warranted.

Characterization of the immune microenvironment in matched primary and metastatic breast cancer lesions from the AURORA study: BIG 14-01.

1009 Background: Immunotherapy benefit in patients with metastatic breast cancer (MBC) is limited to patients with triple negative breast cancer and PD-L1 expression in the tumor sample. Multi-omics characterization of the anti-cancer immune response in MBC could provide novel insights into the mechanisms behind immune response failure. Methods: The AURORA program (NCT02102165) enrolled patients with MBC who received at most one line of treatment in the metastatic setting. RNA sequencing was performed on primary and metastatic lesions. Stromal tumor infiltrating lymphocytes (sTIL) were scored in line with the International Immuno-Oncology Biomarker Working Group for Breast Cancer recommendations. T cell and B cell receptor (TCR and BCR) analysis was performed with MiXCR. Deconvolution of bulk RNA sequencing data was performed using xCell. ImmuneScore-normalized Relative Abundance metastasis/primary Ratios (RAR) of immune cell types were calculated. All comparisons between primary and metastatic lesions were performed on matched samples. Wilcoxon signed-rank tests were used. Results: As expected, sTILs decreased from primary to metastatic lesion. However, 9% of metastatic lesions still had ⪰20% sTILs. Matched RNA expression data was available for 204 patients. Relative abundance of macrophages (RAR 3.3, p&lt;0.001) and Th1 cells (RAR 1.5, p&lt;0.001) was increased in the metastases, while Treg cells (RAR 0.12, p&lt;0.001), CD8+ T cells (RAR 0.32, p&lt;0.001) and B cells (RAR 0.32, p&lt;0.001) decreased the strongest. Metastases with ⪰20% sTILs had higher Treg cells (p&lt;0.001) and B cells (p&lt;0.001) compared to metastases with low sTILs, which had more Th1 cells (p&lt;0.001), mast cells (p&lt;0.001) and NKT cells (p&lt;0.001). De novo metastatic and synchronous primary samples had more BCR (p&lt;0.001) and TCR (p&lt;0.001) clones in common as compared to non-de novo metastatic cancers. Conclusions: sTIL percentage decreased from primary tumor to metastatic lesion. Metastatic lesions with many sTILs (⪰20%) were enriched for immune response suppressing regulatory T cells. [Table: see text]

Correlation between biomarkers and treatment outcomes in diverse cancers: a systematic review and meta-analysis of phase I and II immunotherapy clinical trials

BackgroundMany immuno-oncology (IO) trials are conducted without biomarker selection. We performed a meta-analysis of phase I/II clinical trials evaluating immune checkpoint inhibitors (ICIs) to determine the association between biomarkers and clinical outcomes, if any. MethodsA PubMed search for phase I/II clinical trials with drugs approved by the Food and Drug Administration (labelled, off-label, combined with investigational ICIs or other treatment modalities) from 2018 to 2020 was performed. The objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) were compared between biomarker-positive and biomarker-negative groups, using studies that explored the correlation of biomarkers with outcomes. ResultsOverall, 174 clinical studies that included 19,178 patients were identified, and 132 studies investigated>30 correlative biomarkers that included PD-L1 expression (≥1%, 111 studies), tumour mutational burden (20 studies) and microsatellite instability/mismatch repair deficiency (10 studies). Overall, 123, 46 and 30 cohorts (drugs, tumour types or biomarkers) with 11,692, 3065, and 2256 patient outcomes for ORR, PFS and OS, respectively, were analysed in correlation with biomarkers. Meta-analyses demonstrated that ICIs in patients with biomarker-positive tumours were associated with higher ORR (odds ratio 2.15 [95% CI, 1.79–2.58], p < 0.0001); and longer PFS (hazard ratio [HR] 0.55 [95% CI, 0.45–0.67], p < 0.0001), and OS (HR 0.65 [95% CI, 0.53–0.80], p < 0.0001) compared with those with biomarker-negative tumours. Significance for ORR and PFS was retained in multivariate analysis (p < 0.001) (OS, not included owing to the small number of trials reporting OS). ConclusionOur data suggest that IO biomarkers should be used in patient selection for ICIs. Prospective studies are warranted.

Abstract 2322: Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers

Abstract Cytokines have a large impact on the tumor microenvironment by affecting cell growth, survival, inflammation, and differentiation. Understanding the spatial biology within the tumor microenvironment, including the cytokine organization within specific cell types, can lead to better treatment plans for patients. We developed a hybrid multiplex panel, using RNA in-situ hybridization (ISH) and immunofluorescence (IF) to investigate the spatial biology of the tumor microenvironment. This panel also enabled us to simultaneously detect the RNA of cytokines and protein of specific immuno-oncology (IO) biomarkers. This allows us to visualize spatially, not only the organization of cell types but also to identify the cellular sources of specific cytokines. In this study, we analyzed the tumor microenvironment of samples from non-small cell lung cancer (NSCLC) and breast cancer in two panels for cytokine RNAs and IO protein biomarkers. Panel 1 included TNFa and IL-2 cytokines combined with the CD68 and CD163 IO protein biomarkers. Panel 2 consisted of IL-6 and IL-2 cytokines with the PAX5 and CD3 IO protein biomarkers. Staining was completed on the Leica Bond RX autostainer, and slides were scanned using the PhenoImager™ Fusion. Visiopharm® software was used to analyze the tumor microenvironment of tissue samples and localize cytokines in specific cell types. CD163 positive macrophages (M2 phenotype) were seen predominantly within the tumors (NSCLC and breast cancer) whereas CD68 positive macrophages were identified towards the periphery in the non-tumor microenvironment. NSCLC tumor cells showed higher expression levels of IL-2, IL-6 and TNFa compared to breast cancer tumor cells. Predominance of CD3 positive T cells was noted with relative lack of PAX5 positive B cells within both NSCLC and breast cancer tumors. Multiplexing enabled assessment of relative expression levels of IL-2, IL-6 and TNFa in T lymphocytes and macrophages and TNFa in dendritic cells. Our hybrid multiplex panel can provide insights into the visualization of spatial organization of tumor microenvironment. It also enables semi-quantitative assessments for the expression levels of cytokines and their relative expression within tumor and immune cells, thereby helping to correlate response to treatment, especially with checkpoint inhibitors. Citation Format: Brenna Dennison, Stephanie Allen, Bhavika Patel, Jacob Stapleton, Roni Archuleta, Mary Lou Rath, Navi Mehra, Sameer S. Talwalkar. Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2322.

Combining the guidelines-method and multiphoton imaging method to improve the prognostic value of tumor-infiltrating lymphocytes in breast cancer.

Multiphoton microscopy (MPM) was introduced to label-freely obtain tumor-infiltrating lymphocytes (TILs) images from a total of 611 patients, and the prognostic value of TILs in breast cancer was assessed by the MPM method (TILs-MPM) and guidelines-method proposed by the International Immuno-Oncology Biomarker Working Group (TILs-WG), respectively. Moreover, the clinical (CLI) model, TILs-WG+TILs-MPM model, and full model (CLI+TILs-WG+TILs-MPM) were developed to investigate the prognostic value of TILs. The results show that TILs-WG performs better in ER-negative subgroup, and TILs-MPM is comparable with TILs-WG in the ER-negative subgroup, but has the best performance in the ER-positives subgroup. Furthermore, the TILs-WG+TILs-MPM model can significantly improve the prognostic power compared with the TILs-WG model, and the full model has excellent performance, with high AUC and HR in both ER-positive, ER-negative subgroups, and the complete cohort. Our results suggest that the combination of TILs-WG with TILs-MPM model can greatly improve the prognostic value of TILs.

Abstract 5595: Serial monitoring of circulating tumor cells and circulating tumor DNA in metastatic lobular breast cancer identifies intra-tumor heterogeneity and precision and immuno-oncology biomarkers of therapeutic importance

Abstract Precision and immuno-oncology clinical decisions are based on predictive biomarkers. Circulating biomarkers offer a minimally invasive approach to monitor intra-patient tumor heterogeneity and detect in real-time the clinically-relevant evolving clonal architecture. Although currently underutilized, single-cell DNA next generation sequencing of circulating tumor cells (CTC) is a particularly suitable method to complement tissue and circulating tumor DNA (ctDNA). Here we analyzed 113 individual CTC, 21 ctDNA, 15 white blood cells (WBC) samples and 15 tissue biopsies, from 15 CTC-positive lobular breast cancer patients. CTC were enriched with the CellSearch® system and isolated as single cells with the DEPArray™ system. CTC, WBC, and ctDNA underwent scNGS with the Oncomine Comprehensive Assay covering ~500 genes and 1.1Mb of genomic space to detect mutations, copy number alterations, tumor mutation burden (TMB) and microsatellite instability (MSI). 99.1% of single cells and 95.2% of ctDNA samples were informative. Our CTC-based precision medicine reporting platform, MI-CTCSeq, detected CTC in 9 of 15 patients (60%) with FDA-approved actionable alterations including in the oncogenes PIK3CA and FGFR2 and HER2. 3 of these 9 (33%) harbored actionable alterations not shared between all 3 analyte types (tissue, CTC and ctDNA) including 3 actionable mutations found in CTC and ctDNA only, 1 in tissue and ctDNA only, and 1 in ctDNA only. Two of those ctDNA mutations were identified near the limit of detection and with a priori knowledge from tissue or CTC. Interestingly, 1 patient with plentiful CTC had no detectable ctDNA. Another patient’s tissue biopsy was inadequate for sequencing while both liquid biopsy analytes were abundant. 13 patients (87%) displayed intra-patient, inter-CTC genomic heterogeneity of driver mutations. 1 of 4 (25%) patients with CTC available in &amp;gt;1 timepoint displayed fluctuations in their CTC subclonal makeup between timepoints. Data from this patient’s 2 tissue biopsies, 4 ctDNA samples, and 27 individual CTC over 6 timepoints, combined to reveal in unprecedented detail inter-metastatic lesion and inter-CTC heterogeneity and evolution in response to endocrine, chemo and immunotherapy selective pressures. In a novel approach we show detection of single-cell CTC TMB and MSI. CTC TMB was highly concordant (R 0.81) with the corresponding tissue biopsies. Further, in a novel observation, we detected intra patient, inter-CTC heterogeneity of TMB and MSI, which has potential implications for immunotherapy response and development of resistance. Taken together, these data support the non-invasive biomarker interrogation and monitoring by liquid biopsy that incorporates CTC to complement tissue in informing treatment approaches. Citation Format: Andi K. Cani, Emily M. Dolce, Kevin Hu, Chia-Jen Liu, Elizabeth P. Darga, Dan Robinson, Yi-Mi Wu, Dafydd G. Thomas, Costanza Paoletti, Scott A. Tomlins, James M. Rae, Aaron M. Udager, Arul M. Chinnaiyan, Erin F. Cobain, Daniel F. Hayes. Serial monitoring of circulating tumor cells and circulating tumor DNA in metastatic lobular breast cancer identifies intra-tumor heterogeneity and precision and immuno-oncology biomarkers of therapeutic importance. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5595.

Abstract 2120: Exploring the genomic landscape of colorectal cancer for enabling clinical genomics informed and real-world data based clinical development

Abstract Background: Activation of the MAPK-signaling by RAS- (KRAS or NRAS) alterations is an important driver event in colorectal cancer (CRC) tumorigenesis that determines treatment selection (1).Real-world data (RWD) mining is an important tool to inform patient selection and stratification (2,3). Here, RWD genomics data mining was conducted using the Foundation Medicine database to explore RAS and BRAF-alterations in CRC patients and to investigate the general alterations’ landscape - including rare alterations. The prevalence of microsatellite instability (MSI) and tumor mutational burden (TMB) were also explored. Methods: The prevalence of gene alterations and their co-occurrence with RAS/BRAF-alterations in tumor tissue of CRC patients (N=42800) were investigated using the FoundationInsightsTM web platform, which includes harmonized results from the FoundationOneCDx, FoundationOneHeme, and PD-L1 assays from 2012 to March 2022. Data was collected from FMI solid and heme tests from 2012 to March 2022. Alterations that render a particular gene ‘altered’ included single nucleotide variants (SNVs) or insertion-deletion mutations (Indels), collectively referred to as short variants (SVs), rearrangements (RE) and copy number events (CN). TMB (cut-off 10 mut/MB) and MSI status were also characterized. Results: Altogether, 36.9% of CRC samples were RAS/BRAF-WT and 63.1% had a known or likely functional RAS/BRAF-alteration, respectively. Of all KRAS and NRAS alterations (SV, CN and RE regardless of annotation as functional or presence in a hotspot), SVs in exons 2, 3 and 4 constituted 96.1% and 94.2% of all alterations, respectively. Relative to all samples the potentially targetable KRAS p.G12C, p.G12D and p.G12V mutations were present in 3.6%, 15.1% and 10.2% of samples, respectively. The p.G12E variant was present in less than ten samples. The five most frequently altered potentially targetable genes were PIK3CA (19.6%), PTEN (8.7%), ERBB2 (4.7%), EGFR (2.5%) and FGFR1 (2.0%). NTRK-alterations (NTRK1/2/3) were present in 0.9%, ROS1-alterations in 0.4%, RET-alterations in 0.6% and ALK-alterations in 0.5% of samples, respectively. The prevalence of immuno-oncology biomarkers was also explored; overall, 9.6% of samples were TMB-high, 6.1% MSI-high and 0.6% POLE-altered. MSI-high or TMB-high samples were significantly more abundant in the RAS/BRAF-altered subset. In the RAS/BRAF-WT subset 4.6% were MSI-high and 7.9% TMB-high, whereas in the RAS/BRAF-altered subset 7.1% were MSI-high and 10.6% TMB-high. Conclusion: RWD based clinical genomic profiling confirms that the vast majority of RAS-alterations in CRC are SVs in exons 2, 3 and 4. Both TMB-high and MSI-high samples are significantly more abundant in the RAS/BRAF-altered cohort. RWD confirms that PI3K-, ERBB- and FGFR-signaling pathways are frequently altered in CRC. RWD based clinical genomic profiling has the potential to support comprehensive clinical study design as well as patient selection/stratification. Citation Format: Markus Schulze, XiaoZhe (Janet) Wang, Jawad Hamad, Julia F. Hopkins, Julia F. Hopkins, Jürgen Scheuenpflug, Zheng Feng. Exploring the genomic landscape of colorectal cancer for enabling clinical genomics informed and real-world data based clinical development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2120.